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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.About the TeamRead more about the research team's work here: https://decagon.ai/blog/introducing-decagon-labs The Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.About the RoleAs a Staff Research Engineer, you’ll be responsible for building industry-leading conversational AI models that power Decagon’s agent, and taking them all the way from idea to production. You’ll own multi-quarter initiatives that push the agent’s reliability, capability, and efficiency forward, and you’ll design and implement frontier approaches for training, evaluation, and orchestration across the system.We’re looking for strong engineers who want to build the core models and algorithms behind our AI agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.In this role, you willLead research and engineering efforts to improve core conversational capabilities in production, including instruction following, retrieval, memory, and long-horizon task completionBuild and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experiencePartner with platform and product engineers to integrate new models into production systemsBreak down ambiguous research ideas into clear, iterative milestones and roadmaps.Mentor other researchers/engineers, set technical direction, and establish best practices for applied research and engineeringYour background looks something like this8+ years of experience in AI/ML engineering or research.Prior experience post-training and deploying LLMs in production environments.Fluency in Python and modern ML tooling (training, evaluation, data pipelines)Track record of taking research ideas from prototype → reliable, measurable production impactAbility to define a roadmap, break ambiguity into milestones, and lead cross-functional executionCompensation$325K – $425K + Offers EquityBenefitsWe proudly offer the following benefits for our full-time employees:Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)Medical, Dental, and Vision benefits for you and your familyLife Insurance and Disability BenefitsRetirement Plan (e.g., 401K, pension)Parental LeaveFertility and family building benefits through CarrotDaily lunches and snacks in the office to keep you at your bestThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.About the TeamThe Infrastructure team builds and operates the foundations that power Decagon: platform, model inference, compute, data, and developer experience. We partner closely with product, research, and applied AI teams to deliver high-scale, low-latency systems with clear SLOs and great developer ergonomics.We organize around a couple of focus areas:Platform: The foundational cloud stack — networking, compute, storage, security, and infrastructure-as-code — to ensure reliability, scale, and cost efficiency. CI/CD, paved paths, and core services that make shipping fast, safe, and consistent across teams.ML & Data: Streaming/batch data platforms powering analytics/BI and customer-facing telemetry, including for customer-managed and on-prem environments. Realtime databases that enable low-latency agents. GPU and model-serving platforms for LLM inference with multi-provider routing.Our mission is to deliver magical support experiences — AI agents working alongside humans to resolve issues quickly and accurately.About the RoleWe're looking for a hands-on Engineering Manager to lead the AI & Data Infrastructure team. This is a deeply technical player/coach role that sits at the core of how Decagon's agents think, respond, and learn. You'll lead the team responsible for the data and inference systems that every agent interaction depends on — from the streaming and batch pipelines that power analytics and customer-facing telemetry, to the realtime databases that back low-latency agent behavior, to the GPU and model-serving platforms that route LLM inference across multiple providers.You'll stay close to the code and systems — reviewing designs, participating in incident response, and contributing directly when it helps the team move faster. You'll also lead by example on AI-assisted engineering, setting the standard for how the team uses AI coding tools to ship higher-quality work more quickly.You'll hire and develop a high-performing team while partnering closely with Research, Product Engineering, Platform, and customer-facing teams to make shipping fast and safe — across our primary cloud as well as the single-tenant and on-prem environments we operate for regulated enterprise customers. Success requires strong people leadership, crisp execution across concurrent enterprise and research commitments, and the technical depth to make sound architectural calls under real constraints.In this role, you willBuild, lead, and develop a high-performing team of data and ML infrastructure engineers, including hiring, coaching, and performance management.Own the technical strategy and roadmap for Decagon's AI & Data Infrastructure — streaming/batch data, realtime databases, and the GPU and model-serving stack powering LLM inference.Stay hands-on: review designs and PRs with depth, lead architecture for hard problems, and contribute code when the team needs it.Drive architecture for high-throughput data systems and low-latency inference, including multi-provider LLM routing and CDC pipelines at scale.Set reliability, quality, and cost standards — data freshness SLOs, inference latency and availability, GPU and analytical cost discipline — and build an operating cadence that keeps the platform healthy as we scale.Invest in developer and analyst experience — paved paths for producing and consuming data, and evals and observability for inference.Raise the bar on AI-assisted engineering: define how your team uses AI coding tools to ship faster with higher quality, and build the workflows and guardrails that make this durable.Partner with Research, Product Engineering, Platform, and customer-facing teams to deliver data and inference capabilities on aggressive timelines, including for enterprise deployments.Your background looks something like this2+ years of engineering management experience leading high-performing data, ML, or infrastructure teams, with a strong IC background before that.Deep technical depth in streaming/batch processing, analytical databases, or model-serving — you're comfortable dropping into the codebase and shipping a PR.Hands-on experience operating large-scale data systems (Kafka, ClickHouse/Snowflake/BigQuery, Postgres at scale) and/or production model-serving infrastructure on GPUs.Familiarity with cloud platforms (AWS, GCP, or Azure), Kubernetes, and infrastructure-as-code.A track record of delivering multi-quarter data or ML infrastructure initiatives through ambiguity.A strong point of view on AI-assisted engineering — you use the tools yourself and have opinions on where they work.Care deeply about engineering craft, operational excellence, and cost discipline. Even better if you haveExperience operating LLM inference infrastructure in production — GPU capacity planning, multi-provider routing, and inference evals.Experience with realtime analytics engines (ClickHouse, Pinot, Druid) and CDC pipelines at scale.Experience delivering data and ML systems into single-tenant, on-prem, or air-gapped enterprise environments.Experience building internal tooling or agents that use LLMs to accelerate engineering work.Background in security and compliance frameworks (SOC 2, PCI DSS, FedRAMP, or similar). Compensation$280,000 - $430,000 + Offers EquityBenefitsWe proudly offer the following benefits for our full-time employees:Take what you need vacation policy (subject to local requirements; UK employees receive 25 days of statutory leave)Medical, Dental, and Vision benefits for you and your familyLife Insurance and Disability BenefitsRetirement Plan (e.g., 401K, pension)Parental LeaveFertility and family building benefits through CarrotDaily lunches and snacks in the office to keep you at your bestThese benefits are described in more detail in Decagon’s policies, may vary by location, and can change at any time according to applicable compensation and benefits plans.

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About Distyl AI Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations — both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations — from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s. The results reflect this approach: a 100% production deployment success rate for our customers and one of the few enterprise AI companies to run a profitable business.What We Are Looking ForAt Distyl, we build AI systems using Evaluation-Driven Development—an approach where evaluation is not an afterthought, but the primary mechanism for iterating, improving, and trusting AI behavior in production.AI Evaluation Engineers focus on designing and implementing the evaluation systems that drive this process. They are hands-on engineers who write production Python code, build evaluation pipelines, and use structured signals to guide system design, prompt iteration, and deployment decisions for real customer-facing AI systems.This role is for engineers who believe that AI systems only improve when measurement is tightly coupled to development—and who want to apply that philosophy directly to systems that matter.Key ResponsibilitiesDesign and implement evaluation frameworks that enable Evaluation-Driven Development for AI systems deployed in customer environmentsDefine how system quality is measured in each domain, ensuring that evaluation signals reflect real user needs, domain constraints, and business objectivesBuild and maintain golden test cases and regression suites in Python, using both human-authored and AI-assisted test generation to capture critical behaviors and edge cases. These test suites are treated as first-class system components that evolve alongside the AI system itselfDevelop and maintain evaluation pipelines—offline and online—that integrate directly into system iteration loops. Evaluation results inform prompt design, agent logic, model selection, and release readiness, ensuring that system changes are driven by measurable improvements rather than intuition aloneDefine, calibrate, and operate LLM-based graders, aligning automated judgments with expert human assessments. They investigate where evaluation signals diverge from real-world outcomes and refine grading approaches to maintain signal quality as systems and domains evolveWork closely with Forward Deployed AI Engineers, Architects, Product Engineers, AI Strategists, and domain experts to ensure evaluation frameworks meaningfully guide system development and deployment in productionWhat We Require2+ years of software engineering experience Strong Python Engineering Skills: Write clean, maintainable Python and are comfortable building evaluation and experimentation pipelines that run in production environments. You treat evaluation code with the same rigor as application codeExperience with Evaluation-Driven or Experiment-Driven Development: Experience using structured evaluation or experimentation frameworks to drive system iteration, and understand the pitfalls of overfitting to metrics that don’t reflect real outcomesAbility to Translate Human Judgment into Code: Work with subject matter experts to elicit high-quality judgments and encode them into test cases, scoring functions, and graders that scaleSystems-Oriented Mindset: Understand how evaluation interacts with prompts, agents, data, and deployment. You design evaluation systems that support fast iteration while maintaining trust and safety in productionAI-Native Working Style: Use AI tools to generate tests, analyze failures, explore edge cases, and accelerate debugging and iterationTravel: Ability to travel 25-50%What We OfferThe base salary range for this role is $150K – $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package100% covered medical, dental, and vision for employees and dependents401(k) with additional perks (e.g., commuter benefits, in‑office lunch)Access to state‑of‑the‑art models, generous usage of modern AI tools, and real‑world business problemsOwnership of high‑impact projects across top enterprisesA mission‑driven, fast‑moving culture that prizes curiosity, pragmatism, and excellenceDistyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in‑office..We’re grateful for the strong interest in this role. The best way to get your profile in front of our team is to apply directly through our careers page, where all applications are reviewed. Due to the high volume of interest, we’re not able to review or respond to all direct emails or LinkedIn messages. We will be in touch with every applicant once we’ve completed our review, regardless of the decision.

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Team Description OpenAI is looking for exceptional researchers to join the Post-Training Frontiers team, which is responsible for post-training the agentic models we ship across Codex, the API, ChatGPT Thinking, and ChatGPT Pro. The Post-Training Frontiers team sets up the pipeline for deciding which integrations can go into the post-training run, develops its own horizontal improvements to the model, and trains the final model.The role requires working on the most impactful horizontal improvements for the next model, which could include factuality, instruction following, function calling, multi-agent collaboration, calibrated reasoning effort, tool use, or improving taste in our models. You might build or improve our grading stack, improve our user-data flywheel, or automate our processes to make large post-training runs faster, more reliable, and easier for researchers to use.This is a team for people who want their work to land directly in models used by hundreds of millions of people. The right person is deeply technical, highly independent, goal-oriented rather than method-oriented, and excited by the messy, high-agency work of turning research ideas into production model behaviorIn this role, you will:Own end-to-end research and engineering projects that improve the final post-training of OpenAI’s agentic models.Decide, together with partner teams, which integrations are ready for inclusion in major model runs.Develop horizontal model improvements across factuality, instruction following, tool/function calling, multi-agent behavior, reasoning-effort calibration, and other broad capabilities.Build and improve training, evaluation, grading, and data infrastructure for large-scale RL/post-training runs.Create evals and diagnostics that help us understand whether a model is ready to ship.Improve the feedback loop from real product usage into post-training, including better ways to learn from implicit user feedback.Collaborate closely with Codex, API, ChatGPT, product, training, and other post-training teams to make frontier models more useful, reliable, and agentic.You might thrive in this role if you:Have strong ML fundamentals and hands-on experience with LLMs, RL, RLHF, post-training, evals, or model training.Are an unusually strong engineer who can move quickly in complex systems and make pragmatic technical decisions.Can own ambiguous problems end-to-end without needing a tightly specified roadmap.Care more about impact than method, and are happy to do unglamorous but load-bearing work when it matters.Have excellent taste in model behavior and can reason about what “good” looks like across many user-facing domains.Are comfortable working across research, infrastructure, data, evals, and product boundaries.Are excited to train and ship the frontier agentic models that power Codex, ChatGPT, and the API.Nice to have:Experience with large-scale model training or RL systems.Experience building evals, graders, reward models, or data pipelines for LLM training.Experience with coding agents, tool-using agents, browser/computer-use agents, function calling, or multi-agent systems.Background in quant, systems, infra, or other environments where you built reliable machinery for high-stakes experimentation.Evidence of strong product taste, especially around writing, design, code generation, or agent workflows.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the TeamOur mission at OpenAI is to discover and enact the path to safe, beneficial AGI. To do this, we believe that many technical breakthroughs are needed in generative modeling, reinforcement learning, large scale optimization, active learning, among other topics.The Scaling team builds robust and scalable software and hardware to support our research efforts. It also offers core development services for mission critical goals and applications. We’re expanding our team to work more closely with our partners on hardware optimization and co-design, and are looking for engineers who cut across the stack from at scale ML model/workload understanding through system architecture to microarchitecture. This team will be responsible for working with partners to optimize their hardware for our workloads from early concept stage through production.About the RoleWe are seeking an experienced SoC Architect to lead the definition and development of next-generation custom AI silicon for edge deployments. This role will be responsible for shaping the architecture of highly efficient, high-performance SoCs optimized for machine learning inference and on-device intelligence.You will work cross-functionally with internal engineering teams and external ecosystem partners to translate product requirements into scalable silicon solutions, driving execution from concept through delivery.In this role you will:Define the architecture and technical roadmap for custom SoCs targeted for edge applications.Drive system-level tradeoff analysis across compute, memory, interconnect, power, thermal, and cost constraints.Architect energy-efficient ML compute subsystems optimized for inference workloads and real-world deployment environments.Collaborate with internal hardware, software, systems, and product teams to align architecture with platform needs.Partner with external silicon vendors, IP providers, and manufacturing partners to execute development plans.Lead hardware/software co-design efforts to maximize performance per watt and end-to-end system efficiency.Guide implementation teams through microarchitecture, RTL development, validation, and bring-up phases.Operate effectively in agile development environments and help teams deliver against aggressive schedules and milestones.You might thrive in this role if:Proven experience defining and delivering complex SoC or ASIC architectures from concept to production.Deep understanding of AI/ML accelerators, edge inference workloads, and energy-efficient compute design.Strong knowledge of SoC subsystems including CPU/GPU/NPU architectures, memory hierarchies, interconnects, and power management.Experience working with both internal engineering organizations and external strategic partners.Ability to lead cross-functional teams in fast-paced, execution-driven environments.Strong communication skills with the ability to influence technical direction across organizations.Preferred QualificationsExperience with edge AI devices, embedded systems, or consumer hardware platforms.Background in performance modeling, silicon cost optimization, and workload-driven architecture.Familiarity with advanced process nodes and modern semiconductor development flows.To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About Norm AiNorm Ai, the leading Legal & Compliance AI company, has a client base with a combined $30 trillion in assets under management. By turning legal code into AI code, Norm enables enterprises to move faster and more comprehensively in their legal and compliance processes with reliability and trust.Norm’s platform combines frontier AI, proprietary legal reasoning systems, and embedded legal and regulatory expertise.We have recently raised more than $140 million, backed by Blackstone, Bain Capital, Vanguard, Citi, New York Life, TIAA, Coatue, Craft Ventures, Henry R. Kravis (KKR co-founder), and Marc Benioff (Salesforce CEO).Norm Ai pioneered Legal Engineering, the process that empowers lawyers to build and supervise domain-specific AI agents with Norm’s proprietary suite of no-code software tools. We hired dozens of lawyers from premier U.S. law firms and trained them as Legal Engineers, who specialize in Large Language Model powered legal workflows.Norm Ai technology is deployed inside many of the largest and most consequential institutions in the world. The company is growing quickly and hiring across all teams. AI Fluency: Norm Ai expects all team members to be fluent in AI. Successful candidates actively use AI in their day-to-day work to support thinking, creation, and problem-solving. They use it to improve the quality and speed of their work and to continuously refine how work gets done end-to-end. Candidates should be prepared to demonstrate and discuss their AI usage throughout the interview process, including concrete examples of tools, workflows, and outcomes. We look for practical, hands-on experience, not theoretical familiarity.This Role:As an Engineering Manager at Norm AI, you will lead a high-performing, multidisciplinary team building the systems that power our AI products — from LLM-based workflows to the infrastructure that supports them in production.Your team will include engineers working across AI and platform domains. You will focus on building a strong, effective team: setting clear priorities, supporting engineers in their growth, and ensuring consistent execution across complex, cross-functional work.You will partner closely with technical directors, senior engineers, legal engineers, and product teams across Norm AI and Norm Law, our first-of-its-kind agentic AI law firm.This role is ideal for an Engineering Manager who thrives in technically complex environments and is energized by leading teams working on challenging problems, even if they are not the primary architect or domain expert.You Will:Lead, mentor, and grow a team of engineers across AI and platform disciplines through regular 1:1s, performance management, and career development.Create clarity around priorities, goals, and execution across multiple workstreams, ensuring the team delivers consistently and effectively.Partner closely with technical leads and senior engineers who own system architecture and design across AI and platform systems.Support engineers working on complex technical problems by providing guidance, removing blockers, and fostering strong collaboration.Establish a high-performance team culture grounded in ownership, accountability, and continuous improvement.Drive team processes including planning, execution tracking, and retrospectives to improve velocity and quality.Lead hiring efforts across AI and platform engineering, partnering with recruiting and technical leadership to attract and close strong candidates.Communicate clearly with senior leadership on team progress, risks, and opportunities.Collaborate cross-functionally with product, legal engineering, and platform teams to ensure alignment and successful delivery.Skills & Experience — Core:4+ years of experience as an engineering manager or in a similar leadership role.Proven track record of managing and developing high-performing engineering teams.Experience leading teams working across multiple technical domains (e.g., backend, infrastructure, data, or AI/ML).Ability to support and mentor engineers working on complex systems, even outside your direct area of specialization.Strong understanding of modern software development practices and system design concepts.Experience driving execution in fast-moving, ambiguous environments.Demonstrated ability to partner effectively with senior engineers and technical leaders.Strong stakeholder management and cross-functional collaboration skills.Excellent communication skills, with the ability to operate effectively with both technical and non-technical audiences.Nice to Have:Exposure to AI/ML systems, such as LLM-based applications or data-driven products.Experience working with cloud infrastructure or platform teams.Background in startups or high-growth environments.Experience in regulated or compliance-heavy domains.What Success Looks Like30 Days:Build strong relationships with team members and cross-functional partners.Gain an understanding of Norm AI’s systems, team structure, and current priorities.Establish clear communication and operating rhythms within the team.60 Days:Drive execution of key initiatives with improved clarity and predictability.Support team members in their development and begin addressing performance gaps where needed.Strengthen collaboration across AI and platform workstreams.90 Days:Demonstrate consistent team delivery across multiple domains.Improve team effectiveness, ownership, and accountability.Establish yourself as a trusted partner to technical leadership and senior stakeholders.Comp and Benefits$240,000–$300,000 a year + generous early employee equity.The range displayed reflects the minimum and maximum target for new hire salary for this position. Within the range, individual pay is determined by job-related skills, experience, and relevant education or training. This range reflects base salary only and does not include equity or benefits.We offer a competitive compensation package including equity, a 401(k) with employer match, and comprehensive insurance (health, dental, hospital, accident, and vision). We provide relocation reimbursement for candidates moving to NYC.We operate in a flexible hybrid model, typically in-office 3–4 days per week.To learn more about Norm Ai, visit our website.

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CarefullCarefull is an AI-powered financial safety platform that helps banks, credit unions, and wealth advisors protect older-adult customers from fraud and money mistakes. We help financial institutions maintain whole-family relationships while protecting their clients. Carefull’s technology addresses senior-specific financial safety challenges: our monitoring detects fraud patterns missed by industry-standard tools, and our features — identity-theft protection, password and document management, communication tools, and how-to content — help customers maintain financial independence while enabling loved ones to step in when needed.The RoleWe are looking for a Data Scientist / AI Engineer to join our Data team to build, evaluate, and improve the AI-powered detection systems at the core of our product. You will work on systems that analyze financial transactions and decide whether to alert a family about potential concerns. This is a hands-on role: you’ll research fraud patterns, design detection logic, write production code, and rigorously evaluate system performance. You will own features end-to-end: from problem understanding to implementation, deployment, and measurement.What You’ll DoOwn end-to-end implementation of AI-driven detection features, from discovery to production deployment and iteration.Design and build data enrichment pipelines to extract structured information from messy, real-world financial transaction data.Research fraud and scam typologies relevant to older adults and translate findings into scalable detection logic.Build evaluation frameworks (metrics, error analysis, model comparisons) to measure system performance and drive improvement.Optimize AI pipelines for accuracy, latency, and cost, making informed tradeoffs on model selection and architecture.Collaborate with Customer Service, Go-to-Market, and partner-facing teams to ensure solutions meet real-world needs and deliver measurable impact.Stay current with developments in LLMs, agent architectures, and applied AI, and identify practical applications for our domain.Who You AreRequiredStrong Python skills with experience building data pipelines and production systems.Hands-on experience with LLMs in production: designing workflows, handling structured outputs, managing context, and evaluating performance.Experience with evaluation methodology: precision/recall tradeoffs, confusion matrices, error analysis, statistical significance.Ability to work with messy tabular data (time series, inconsistent categorical labeling, incomplete records).Comfortable reasoning about ambiguity and building systems that handle context-dependent answers.Clear written and verbal communication in English; able to document reasoning and explain technical decisions to non-technical stakeholders.Strong PlusExperience with LangChain, LangGraph, or similar agent orchestration frameworks.AWS experience (Lambda, CDK, Bedrock, Redshift, DynamoDB).Background in fraud detection, financial services, or risk/compliance.Experience with financial transaction data (ACH, Zelle, wire transfers, POS data, merchant categorization).Familiarity with cost optimization for LLM-based systems at scale.Nice to HaveExperience working with regulated industries or bank partners.Exposure to elder care, aging-in-place, or financial vulnerability research.Background in data science or ML beyond LLMs (statistical modeling, anomaly detection).Interview ProcessSilver Screening interviewTake-home challengeClient technical interviewCTO interviewFinal interview Hiring Manager

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AI at ZapierAt Zapier, we build and use automation every day to make work more efficient, creative, and human. So if you’re using AI tools while applying here - that’s great! We just ask that you use them responsibly and transparently.Check out our guidance on How to Collaborate with AI During Zapier’s Hiring Process, including how to use AI tools like ChatGPT, Claude, Gemini, or others during our hiring process - and when not to.Hi there!Are you excited about building the platform that makes AI and machine learning development faster, safer, and more reliable across an entire company? We’re thrilled to invite you to join Zapier’s AI Platform team as a Sr. Applied AI Engineer!As a key member of this team, you’ll help build and evolve the shared infrastructure that powers AI and ML development across Zapier. The AI Platform team owns the common foundations that product and engineering teams rely on when building with machine learning and generative AI - including systems like our LLM proxy server, observability tooling, and ML Ops platform capabilities.This is a highly leveraged role. Rather than building a single end-user feature, you’ll create the core systems, tooling, and standards that many teams use as their baseline for shipping intelligent products and internal AI-powered workflows. You’ll work at the intersection of platform engineering, applied AI, and developer experience to make it easier for teams across Zapier to build with LLMs and ML systems in a scalable, secure, and production-ready way.Your work will focus heavily on LLM Ops and ML Ops: improving how models are accessed, monitored, evaluated, deployed, governed, and operated in production. You’ll help define the paved road for teams building with AI at Zapier.If you’re passionate about large language models & machine learning, developer platforms, operational excellence, and building the systems that make AI usable at scale, we’d love to meet you!If you’re interested in advancing your career at a fast-growing, profitable, impact-driven company, then read on…Our Commitment to ApplicantsCulture and Values at ZapierZapier Guide to Remote WorkZapier Code of ConductDiversity and Inclusivity at ZapierEven though our job description may seem like we're looking for a specific candidate, the role inevitably ends up tailored to the person who applies and joins. Regardless of how well you feel you fit our description, we encourage you to apply if you meet these criteria:About YouYou have 7+ years of experience in software engineering, with at least 3 of those years dedicated to building distributed, scalable, cloud-based ML/AI systems in production environments. You have strong communication skills, sound engineering judgment, and a track record of building reliable systems that other engineers depend on.You have at least 2 years of experience in LLM Ops, ML Ops, or adjacent platform/infrastructure work. You’re excited by problems like model access, inference reliability, observability, experiment management, evaluations, deployment workflows, governance, and production monitoring.You have experience building shared services, internal platforms, or reusable developer tooling that enable other teams to move faster. You enjoy creating strong abstractions, reducing duplication, and improving standards across an organization.You have experience of working through the full lifecycle of building, testing, deploying, and scaling ML/ LLM architectures.You can identify and document trade-offs made during the development of AI/ML systems. You also have experience building with cloud infrastructure technologies.You love enabling others. You’re energized by building infrastructure and tooling that make product engineers and ML practitioners more effective. You think deeply about developer experience and know that the best platforms are both powerful and easy to adopt.You embody our values. At Zapier, our values are at the heart of how we work together and how we think about our customers. In our remote setting, they help develop trust and ensure we work and collaborate to democratize automation.Things You’ll DoBuild and evolve shared AI Platform capabilities that serve as the foundation for teams building with machine learning and generative AI across Zapier.You will work mostly in TypeScript & Python. Experience isn’t strictly required, but it is a big plus. Comfort with typed languages and modern backend practices is a must.Improve our LLM Ops and ML Ops capabilities, including observability, monitoring, evaluation, deployment workflows, and operational guardrails.Design and implement systems that help teams measure and improve the performance, reliability, safety, and cost efficiency of AI-powered experiences.Proactively identify tooling gaps and work across teams to standardize best practices for building, deploying, and monitoring AI-driven experiences.Collaborate closely with engineers across product, infra, and data teams to ensure our AI components are reusable, well-documented, and easy to adopt company-wide.Evaluate emerging tools, models, and patterns in the AI ecosystem, and help determine which ones should be incorporated into Zapier’s shared platform.Application Deadline:The anticipated application window is 30 days from the date job is posted, unless the number of applicants requires it to close sooner or later, or if the position is filled.Even though we’re an all-remote company, we still need to be thoughtful about where we have Zapiens working. Check out this resource for a list of countries where we currently cannot have Zapiens permanently working.

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About Us: Brilliant Harvest is a fast-growing agtech startup that is redefining how equipment dealerships support their staff and customers. Purpose-built for the ag and construction industries, Brilliant Harvest’s AI-powered platform helps dealership teams find answers faster, save time, reduce downtime, and improve customer service.   Our culture is fast-paced, collaborative, and driven by curiosity. We move quickly, learn constantly, and celebrate progress over perfection. We're looking for dynamic, motivated individuals who are passionate about technology and agriculture to join our team. This is an exciting opportunity to contribute to a meaningful mission while gaining hands-on experience in software development within a fast-growing industry.   If you love building things that matter, enjoy hands-on development, and want to join a team where your work directly shapes the product experience, this is the role for you.   Position Overview:   Note: This opportunity is open to current and continuing students looking to gain internship experience prior to their graduation. A valid co-op and/or work permit is required to work full-time for the duration of the internship. This is a hybrid/remote position, based out of Calgary, AB.   We are looking for a Software Development Associate to assist in the design, development, and implementation of our software and AI powered solutions. As an intern, you will work closely with our engineering team to build and enhance applications that improve agricultural support, from diagnosis and problem solving of issues with agricultural equipment through our AI powered Assistant, automation tools and data analytics platforms. This is an ideal opportunity for a student with a passion for technology and a keen interest in the agricultural space.Key Responsibilities: Collaborate with senior developers to design, build, and test software solutions that address the needs of the agricultural sector. Contribute to coding, debugging, and documenting software applications. Assist in the development of new features, from initial concept to deployment. Assist in research and development for improvements to our AI powered Assistant. Help optimize and improve the performance of existing software systems. Participate in code reviews and contribute to improving development processes and best practices. Test software functionality and troubleshoot issues as they arise. Collaborate with cross-functional teams, including product managers and data scientists, to align technical solutions with business objectives. Stay up to date with the latest trends and technologies in software development and agriculture. Qualifications: Pursuing a degree in Computer Science, Software Engineering, or a related field. Proficiency in one or more programming languages, such as C#, Python, C++, or JavaScript. Familiarity with version control tools (e.g., Git). Strong problem-solving skills and attention to detail. Excellent communication skills and the ability to work well in a team environment. A genuine interest in agriculture, sustainability, and technology. Previous internship or personal project experience related to software development is a plus. Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) or data processing tools is a plus, but not required. Understanding of software development methodologies (e.g., Agile, Scrum) is desirable. What We Offer: Hands-on experience working on real-world projects that have a tangible impact on the agricultural industry. Opportunity to work with a passionate and innovative team in an exciting startup environment. Mentorship and guidance from experienced engineers and leaders in the AgTech space. A collaborative, flexible, and dynamic work environment. Potential for full-time opportunities based on performance. Note: This opportunity is open to current and continuing students looking to gain internship experience prior to their graduation. A valid co-op and/or work permit is required to work full-time for the duration of the internship. This is a hybrid/remote position, based out of Calgary, AB.

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We're looking for a Senior Full Stack Software Engineer who is passionate about building high-quality software in an AI-native way. Someone who treats Claude and the latest agentic coding tools as a core part of their craft, not a novelty. In this role, you will own technical delivery end-to-end, from shaping the architecture of ML-powered applications to leading implementation across cloud services, APIs, and modern front-end frameworks, with Claude Code, the Claude Agent SDK, and the Claude API woven into how you design, build, and ship. You will act as the technical backbone of your project pod, balancing hands-on development with technical leadership, architectural decision-making, and client-facing collaboration. You'll lead epic-level solution design, mentor developers on how to get the most out of Claude in their day-to-day workflows, contribute to shared internal frameworks and skills/plugins, and help shape how we evaluate and deploy emerging AI engineering tooling. You will thrive in this role if you are: A builder at heart who leans on Claude Code to spin up prototypes in hours and scale them into production-grade systems with confidence. Fluent in agentic development patterns. Writing good specs for Claude, structuring repos so AI agents can navigate them, reviewing AI-generated code critically, and knowing when to delegate versus when to hand-code. A strong communicator who can translate between business requirements, technical realities, and what modern AI tooling actually makes feasible. A decision-maker who brings clarity to ambiguous technical challenges and can evaluate when an LLM-in-the-loop is the right solution versus traditional software. Excited by ML-enabled product development and eager to bridge software engineering with intelligent automation and agentic workflows. What You'll Do: Reduced Project Risk: Technical risks on projects are significantly reduced through proactive ownership of epic-level technical design, execution, and cross-team dependency resolution accelerated by effective use of Claude for research, code review, and rapid exploration of design alternatives. Improved Technical Decision-Making: The team makes better technology choices through thorough research, evaluation, and documentation of potential solutions, including informed decisions on when and how to apply Claude, MCP servers, and agentic tooling versus conventional approaches. Stronger Client Confidence: Client and stakeholder confidence is increased by leading technical discovery sessions and acting as a technical SME during project discussions, including on the pragmatic use of LLMs and AI-assisted development in client deliverables. Feature & Epic Implementation: Leads implementation for features spanning multiple user stories or services, using Claude Code and agent-driven workflows to accelerate delivery without sacrificing quality. Architecture & Solution Design: Leads the architecture design for moderately complex solutions, often involving multiple services or systems, and chairs technical reviews including architecting LLM-powered features, agent tool integrations, and MCP server designs. AI Engineering Leadership: Champions best practices for working with Claude across the pod, prompt design, skill and subagent creation, context management, MCP integrations, evaluation of AI-generated code, and secure / cost-aware usage of the Claude API. Mentorship & Technical Leadership: Provides technical leadership within the pod, mediates code review disputes, contributes new features and skills to shared AltaML libraries, and assists in the hiring process by conducting technical interviews. Coordinates the work of other engineers and levels them up on modern AI-assisted development. Client Engagement & Discovery: Leads technical discovery sessions with clients to clarify requirements, define technical scope, and identify where Claude-powered features or agentic workflows unlock real product value. Testing & Quality Strategy: Implements higher-level testing strategies, including integration and end-to-end tests for deployed solutions, plus evaluation harnesses for LLM-powered features (regression tests for prompts, agent behaviours, and tool use). What You Bring: Degree or equivalent work experience in Computer Science, Software Development, or similar 5+ years of experience as a full stack developer Demonstrable, hands-on experience using Claude (Claude Code, claude.ai, or the Claude API) as a daily driver for real software engineering work, not just casual chat use Proven skills at taking ideas from conception to production, including shipping features that are partly or fully built with AI-assisted workflows Strong working experience with Cloud Services (ideally Azure) Strong working experience in a modern object-oriented language Strong working experience writing clean, readable, and easily maintainable code, and a clear point of view on reviewing and hardening AI-generated code Experience with Unit and API testing (e.g., xUnit, Postman, or others) Experience working in an agile environment Experience with Docker Proficiency with Version Control systems (VCS), including working effectively with AI agents in a git-based workflow 130,000 - 150,000 a year

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About the companyJoist AI is a technology company revolutionizing the way professionals in the architecture, engineering, and construction (AEC) industry manage marketing and revenue operations. Our AI-powered software streamlines workflows, making it easier for teams to collaborate, innovate, and succeed.About the roleJoist AI is looking for an engineer with 2–4 years of experience to help build the next generation of agentic applications that streamline proposal writing for the AEC industry. These are systems that reason, use tools, remember, and collaborate with users. The stack spans multi-agent orchestration, MCP servers, skills, long-term memory, evals, retrieval, and the plumbing that makes all of it hold up in production. We're looking for someone to help us build it.What you'll doBuild agents as modular, plug-and-play components that slot cleanly into the wider stack.Add memory layers (short-term, long-term, summarization, retrieval-backed) into running systems.Wire up tool integrations, MCP servers, and skills.Own quality of the features you put out: tests, evals, observability, the works.Dig into production traces to understand what the system is actually doing, and close the loop with fixes.Background we're looking for2–4 years of writing production software.Strong Python skills. You write good Python and can tell good Python from bad, especially now that a lot of code comes out of an LLM. Separation of concerns, clean OOP, idiomatic syntax, well-structured modules, tests that actually test something.Solid grounding in core agentic and LLM concepts: RAG, prompting patterns, tool use, structured outputs, streaming, context management, basic generative AI fundamentals.You've built something non-trivial with the modern agent toolkit, whether that's a side project, a prototype at work, or a hackathon thing that got out of hand.Able to drop into an unfamiliar codebase and find your way around fast.A keen eye for detail. You sit with a problem before reaching for a solution. No jumping to the shiny fix because it sounds clever. You understand what's actually broken before you touch anything.Data-driven by default. Decisions come from production traces, eval numbers, and logs, not vibes. Comfortable slicing through trace data to find the real signal.Hands-on experience with Langfuse or LangSmith (or equivalent tracing/observability for LLM systems).Genuine curiosity about the frontier. You read the blog posts, try the frameworks, and have opinions about where agent design is headed.Experience we'd be particularly excited aboutSearch and retrieval: embeddings, vector databases, hybrid retrieval, rerankers, and the gap between a retrieval system that demos well and one that survives real data.LLM evaluations end-to-end: designing evals, choosing what to measure, building the harness, keeping scores honest as models and prompts shift.LangGraph depth: building custom graphs, understanding checkpointers, working with context-management nodes (summarizers, windowing, state pruning) inside larger agent graphs.What to expectWe conduct a rigorous interview process based on integrity, talent, and drive. We trust our teammates from day one and move quickly to evaluate your fit for the role. The entire interview process typically takes two weeks. Here's what to expect:A 30 minute Zoom meeting to talk about Joist AI, your background, and answer any questions about the role. (Getting to know each other)45-minute Python proficiency / agentic coding proficiency test. 2 problems. 1 to be coded by hand. Other using Gen AI.60 min project, deep dive into the work they have done. A short presentation followed by a Q&A. Presentation should conclude between 20-25 min. 45 min interview on Gen AI / LLM fundamentals. 30 min culture fit.

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About AbridgeAbridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. The RoleAbridge is looking for Clinician Scientists to drive the development of our AI-powered clinician tools. We’re looking for someone who can combine deep clinical expertise with a background in AI. In this role, you will help shape AI-driven tools and ensure our models generate accurate, high-quality products that enhance clinician efficiency and patient care. You’ll work closely with engineers, researchers, product managers, and clinicians to refine AI models, validate outputs, and develop new capabilities that improve documentation workflows.Must be willing to work from our SF office at least 3x per weekThis position requires a commitment to a hybrid work model, with the expectation of coming into the office a minimum of three times per week. Relocation assistance is available for candidates willing to move to San Francisco.What You’ll DoDevelop and refine AI-driven clinical tools across notes, risk adjustment (HCC capture), clinical decision support, and prior authorization using clinical expertise and prompt engineeringDefine what “clinically meaningful” output looks like for each product area, including acceptable error rates, failure modes, and quality thresholdsCollaborate with cross-functional teams (engineers, data scientists, clinicians) to integrate medical insights into AI models.Write, review, and optimize prompts to improve AI model performance in clinical contexts.Build and refine evaluation tools to streamline medical documentation quality assessment, including hallucination detection, omission detection, and medication safety checksTranslate clinical needs into technical specifications and data models.Define clinical guardrail metrics and baselines; own pre/post evaluation requirements for any model update that affects clinical outputContribute to product development, revenue cycle management, and broader business initiativesMonitor clinical guideline update cycles and flag when product behavior needs to evolve based on new standards or payer policiesWhat You’ll BringMD, PA, DO (or equivalent clinical degree) with direct experience working in clinical practiceDeep understanding of medical documentation, clinical workflows, and medical terminologyAbility to evaluate AI-generated clinical notes, provide structured feedback, and guide improvementsStrong knowledge of healthcare data standards (e.g., FHIR, HL7) and privacy regulations (e.g., HIPAA)Hands-on experience in clinical data validation and quality assessmentExperience collaborating with engineers and product teams to build AI-powered clinical toolsStrong analytical and problem-solving skillsExcellent written and verbal communication skillsNice to HaveExperience in software engineering, particularly in prompt engineering or AI model developmentPython programming skills and experience with deep learning frameworks such as PyTorch, JAX, and/or TensorFlowPrevious experience in AI-powered clinical documentation tools or clinical decision support systemsPublished research in AI, machine learning, or healthcare technologyWhy Work at Abridge?At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is clear: to power deeper understanding in healthcare. We’re driving real, lasting change, with millions of medical conversations processed each month.Joining Abridge means stepping into a fast-paced, high-growth startup where your contributions truly make a difference. Our culture requires extreme ownership—every employee has the ability to (and is expected to) make an impact on our customers and our business.Beyond individual impact, you will have the opportunity to work alongside a team of curious, high-achieving people in a supportive environment where success is shared, growth is constant, and feedback fuels progress. At Abridge, it’s not just what we do—it’s how we do it. Every decision is rooted in empathy, always prioritizing the needs of clinicians and patients.We’re committed to supporting your growth, both professionally and personally. Whether it's flexible work hours, an inclusive culture, or ongoing learning opportunities, we are here to help you thrive and do the best work of your life.If you are ready to make a meaningful impact alongside passionate people who care deeply about what they do, Abridge is the place for you. How we take care of Abridgers:Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employeesComprehensive Health Plans: Medical, Dental, and Vision coverage for all full-time employees and their families.Generous HSA Contribution: If you choose a High Deductible Health Plan, Abridge makes monthly contributions to your HSA.Paid Parental Leave: Generous paid parental leave for all full-time employees.Family Forming Benefits: Resources and financial support to help you build your family.401(k) Matching: Contribution matching to help invest in your future.Personal Device Allowance: Tax free funds for personal device usage.Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits.Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more.Mental Health Support: Dedicated access to therapy and coaching to help you reach your goals.Sabbatical Leave: Paid Sabbatical Leave after 5 years of employment.Compensation and Equity: Competitive compensation and equity grants for full time employees.... and much more!Equal Opportunity EmployerAbridge is an equal opportunity employer and considers all qualified applicants equally without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.Staying safe - Protect yourself from recruitment fraudWe are aware of individuals and entities fraudulently representing themselves as Abridge recruiters and/or hiring managers. Abridge will never ask for financial information or payment, or for personal information such as bank account number or social security number during the job application or interview process. Any emails from the Abridge recruiting team will come from an @abridge.com email address. You can learn more about how to protect yourself from these types of fraud by referring to this article. Please exercise caution and cease communications if something feels suspicious about your interactions. 

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Why you should join usTandem is a generational opportunity to rethink how we bring new therapies to market, and our path to doing so is significantly de-risked – we have:Exponential organic growth: We have product-market fit and are growing rapidly. Tandem supports thousands of new patients every day, is spreading with doctors through word-of-mouth, and works with the largest biopharma companies in the world.An AI-first business model: Our approach is distinctly enabled by AI, but our business gets stronger (not commoditized) as foundation models improve. We are building durability through two-sided network effects that compound over time.Top tier investors: With the traction to support conviction in our model, we raised significant funding from top investors (Thrive Capital, General Catalyst, and Accel) to build an exceptional team of engineers and operators.Our number one priority is scaling to market demand. We are looking for individuals who are high horsepower, high throughput, and hyper resourceful to help us increase capacity and grow. We move fast and need to move faster.All full-time roles are in person in New York. You can learn more about working with us in the last section of this page.About the roleAs a Research Engineer on our team, you will work on real production use cases of LLMs and other ML techniques to solve business problems and create groundbreaking AI applications. The role requires that you develop a deep understanding of our product surface area and what drives our business, such that you can operate and drive impact both cross-functionally and independently. You will have end-to-end responsibility for projects, including definition, design, development, launch, and success––this includes ensuring your output has the expected impact on user growth, operational efficiency, or revenue generation.This is a demanding role, with a high level of autonomy and responsibility. You will be expected to "act like an owner" and commit yourself to Tandem's success. If you are low-ego, hungry to learn, and excited about intense, impactful work that drives both company growth and accelerated career progression, we want to hear from you.If you join, you will:Scope and spearhead AI augmentation and automation projects across our product surface area, including: Unintuitive classifications, Data extraction and summarization, Precise content generation, Reference-based search and question answering, Process outcome prediction, Probabilistic triggering of workflows, and Multimodal LLM-powered botsStay on top of emerging AI methods and guide decisions around which models and techniques to adopt––including evaluating when to use open-source models, proprietary models, and custom fine-tuning approachesEstablish research strategies for various AI methods, including rigorous experimentation and evaluation protocols that account for accuracy, consistency, interpretability, and real-world impactDevelop novel algorithms and techniques to address core research problems in natural language processing, data extraction, and autonomous reasoning (e.g., few-shot learning, agentic reasoning, and multi-modal interaction)Participate actively in client engagements, working directly with customers to understand requirements and deliver innovative solutionsWork closely with the rest of our team and CEO to make business decisions as we balance speed of growth and long-term profitabilityWe need your help to:Decipher and automate complex, branching workflows for insurance coverage, affordability programs, and fulfillmentCombining AI/ML approaches to achieve high precision document classification, unstructured data extraction, and reference-based question answeringAutomating multi-step, path-dependent processes, using a combination of RPA/scraping approaches to navigate and operate third-party platformsBuilding a state machine that drives system decisions and handles failure modes across a set of processes that are technically independent but practically intertwinedScale across a growing range of drug classes, patient populations, and provider marketsMaking our data and ML pipelines robust to variation and inconsistency in input data formats (e.g., clinical documentation structure and style)Leveraging empirical data to build and continuously update our understanding of opaque external systems (e.g., insurance company policies)Creating consumer-grade experiences for patients, physicians, and other users that incorporate intuitive AI-powered workflowsUse our network to help biopharma partners accelerate drug development, launch, and accessTranslating large volumes of heterogeneous data into reliable insights, informing decisions like clinical indication selection, launch markets, and insurer negotiationsDeveloping predictive and simulation models to forecast outcomes such as clinical trial site performance, drug adoption rates, and the impact of rebates/subsidiesUsing real-time data and direct engagement channels to enroll criteria-matching patients and physicians in clinical studies and access programsWe’ll be most excited if you have:Strong programming skills and general Computer Science knowledgeStrong research background in ML/NLP, demonstrated through publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP) or significant open-source contributionsExperience working on complex ML problems (e.g., data-efficient learning, reasoning agents, or multi-step workflows) and deploying those solutions in production environmentsDeep understanding of modern ML methods, including transformer architectures, attention mechanisms, reinforcement learning, and multimodal models — with proficiency in deep learning frameworks such as PyTorch, TensorFlow, or JAXStrong written and verbal communication that allows you to be an effective participant in both internal debates and external relationshipsTrack record of moving quickly, finding shortcuts, and going to unreasonable lengths to deliver on goalsHigh NPS with your former teammatesThis is a list of ideal qualifications for this position. If you don't meet every single one of them, you should still consider applying! We’re excited to work with people from underrepresented backgrounds, and we encourage people from all backgrounds to apply.Working with usTandem is based in New York, with our full team working out of a beautiful and spacious office in SoHo. We run as a high-trust environment with high autonomy, which requires that everyone is fully competent and operates in line with our principles:Commit to audacity. "Whether you think you can, or you think you can't – you're right.”Do the math. Be rigorous, assume nothing.Find the shortest path. Use hacks, favors, and backdoors. Only take a longer road on purpose.Spit it out. Be direct, invite critique, avoid equivocation – we want right answers.Be demanding and supportive. Expect excellence from everyone and offer help to achieve it.Do what it takes to be number 1. We work hard to make sure we win.We provide competitive compensation with meaningful equity (for full-time employees). Everyone who joins early will be a major contributor to our success, and we reflect this through ownership and pay.We also provide rich benefits to ensure you can focus on creating impact (for full-time employees):Fully covered medical, vision, and dental insurance.Memberships for One Medical, Talkspace, Teladoc, and Kindbody.Unlimited paid time off (PTO) and 16 weeks of parental leave.401K plan setup, FSA option, commuter benefits, and DashPass.Lunch at the office every day and Dinner at the office after 7 pm.Our salary ranges are based on paying competitively for our company’s size and industry, and are one part of the total compensation package that also includes equity, benefits, and other opportunities at Tandem (for full-time employees). Individual pay decisions are ultimately based on a number of factors, including qualifications for the role, experience level, skillset, geography, and balancing internal equity. Tandem is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.

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About UsAt Hayden AI, we are on a mission to harness the power of computer vision to transform the way transit systems and other government agencies address real-world challenges.From bus lane and bus stop enforcement to transportation optimization technologies and beyond, our innovative mobile perception system empowers our clients to accelerate transit, enhance street safety, and drive toward a sustainable future. What the job involves As a Senior State Estimation Engineer at Hayden AI, you will be asked to derive and implement novel real-time pose estimation algorithms. Research, develop and implement algorithms to solve large-scale mapping. Collaborate with other engineers to develop algorithms for in-situ and in-factory multi-sensor calibration.ResponsibilitiesContribute to high impact, multidisciplinary projects across teamsProgram and develop software in C++ and/or pythonDerive and implement novel, real-time pose estimation algorithmsResearch, develop and implement algorithms to solve problems such as large-scale mapping, probabilistic object tracking, online/offline sensor calibration and/or vision-based localizationCollaborate with deep learning, device, and cloud teams to improve overall system architecturesProvide mentorship to our junior engineersRequired QualificationsMaster of Science degree or the foreign equivalent in Electrical and Computer Engineering, Robotics, Machine Learning, Computer Science, Electrical Engineering or a related field.Five (5)+ years of experience in the position offered, as a software engineer, software engineer intern, or a related state estimation engineer role.Five (5) years of experience with all of the following: programming in C++; designing and developing software; classical ML, Linear Algebra, Stochastic Processes, Geometric Computer Vision and Optimization (Convex, Nonlinear); Kalman Filter, MAP, Sequential Monte Carlo (particle filter), Nonlinear Least squares, IRLS and MHT; GPS, IMU, camera and wheel odometry.Experience deploying SLAM/VIO estimators in a real-world application.Work with multiple sensors such as GPS, IMU, camera, LIDAR, and wheel odometry.

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About UsAt Hiya, we're making calls safe, useful, and human again. Voice is the most human form of communication, yet it's become one of the least trusted. Spam, scams, and AI manipulation have eroded what was once a simple way to connect. Hiya is changing that.Each month our AI voice technology analyzes 28+ billion calls, protecting over 550 million users and 800+ businesses worldwide. Partnering with a growing global network including, AT&T, Samsung, British Telecom EE, Rogers, MasOrange, Bell Canada, MasMovil, and Virgin Media O2, we're not just stopping bad actors, we're helping people feel good and confident about picking up the phone again.This is a pivotal moment for voice. As new threats and technologies accelerate, so does demand for trusted voice communication. Hiya is growing 40%+ year over year, expanding globally, and defining what voice becomes next.Join us. You won't just work on what voice is today, you'll shape what it becomes tomorrow: smarter, safer, and genuinely worth answering again.About the RoleYou will own features end-to-end. That means holding a piece of work from contract through rollout across whichever surfaces it needs to touch, whether that's our TypeScript/Node backend, the iOS app, the Android app, or all three. Some features live mostly in the API layer. Some require real client work on one or both platforms. The job is to deliver the whole thing, not to hand off the parts that aren't your home surface.This is a builder role. We want someone who likes shipping, can hold a feature from contract through rollout, works across stack boundaries without friction, and gets things in front of real users.What You'll DoIn the first ninety days, expect to:Ship meaningful production code on one of our two products. We care less about scope than about you owning it end to end.Define and defend an API contract with mobile and design before writing the feature behind it, and iterate on that contract as you learn.Develop a point of view on how the team's agentic workflow is serving you, and raise the places where it isn't.What we are looking forThese are habits, not credentials. We will probe them in conversation. We don't care much about your résumé. We care about how you think and execute, and we will test that live in the interview.Full-stack by instinct. You are comfortable moving between the API, the data layer, and the client code that calls it. You have opinions about where logic should live, and you've shipped features where you had to decide whether something belonged on the server, on the client, or at the edge. You don't need to be equally strong on iOS, Android, and backend on day one. You do need to be the kind of engineer who picks up whichever surface a feature requires and ships it, rather than the kind who stops at the boundary of what they already know.Context engineering over prompt engineering. You've internalized that the useful lever usually isn't the prompt, it's what the model sees before the prompt runs. You have opinions about selection, compression, ordering, and isolation of context. You know context rot is real and you have strategies for it.Plan-first on non-trivial work. You don't one-shot real features. You plan, stage, and iterate. You separate exploration from execution. You read plans before you run them, and you edit them. You know why a chain of "good enough" agent decisions stacks into a bad outcome, and you have habits that prevent it.Contracts before code, built with product and design. On meaningful work, the agent does not touch the keyboard until there is a clear contract: what the behavior is, what the acceptance criteria are, what the interfaces look like. That contract is built with product, design, and the engineers who will integrate against it. Agents are literal-minded and will build the wrong thing at speed if the contract is underspecified. You treat the contract as a living artifact, not a PRD you wrote once and forgot about.Multi-model and multi-agent routing. You use different models for different jobs. You're comfortable running agents in parallel on separate worktrees when work decomposes cleanly. You know when to spawn a sub-agent and when to stay in one context, and you can articulate the tradeoff.Taste formed by shipping. You have opinions about which parts of the agentic stack are earning their keep today. You have changed your mind at least once in the last six months. You can defend your current position and tell us when you last updated it.What we do not filter onYears of experience.Familiarity with our exact stack on day one.Leetcode performance.How to applySend a short note, under 500 words, that answers three things.An artifact. Point us at something you have built or meaningfully shaped. A set of skills, a sub-agent you rely on, a slash command library, a hook set enforcing a team quality gate, a rule file with real thought behind it, a contract template that changed how your team works with product. Public repo preferred. Private is fine if you can describe it in enough detail that we can tell it is real.A tension you have resolved. Tell us about a time your agent-assisted workflow produced output that looked right and was actually wrong. What was the failure mode? How did you catch it? What did you change so it wouldn't happen again?Which product do you find more interesting as a problem, and why? You'll work across both Spam Blocker and AI Phone in this role, so this isn't about placement. We want to see how you think about the product space.A link to your GitHub profile is highly encouraged, or other examples of work you can share. Resume is optional in the first round, and we won't read it before we read your response to the questions above.How We WorkHiya is not a passive environment. We expect people to take ownership, form opinions, and engage directly with hard problems.We work with a high degree of transparency and autonomy. Context is shared openly, and decisions are discussed, challenged, and then made. Once a call is made, we commit and move forward.You’ll be expected to work through ambiguity, weigh tradeoffs, and take responsibility for results, while keeping a high bar for quality and customer trust.Every team member at Hiya is expected to live our core values:Serve, our customers and partners by holding a high bar for trust and qualityOwn, share in success and open up to failuresLead, listen, show up with a point of view but commit entirely once a decision has been madeImprove, even if it means changing course or contradicting ourselvesDo, rather than observeBenefits25 holiday plus bank holidaysOpt in salary sacrifice pension scheme (company full 4% of basic salary contribution)Paid parental leavePrivate medical insurance through Vitality (including dental & vision)Employer-paid life insurance 2x base salaryDonation Matching for a charity of your choice (up to $1,000/ year)WFH equipment stipend$1,000/year in Professional Development fundsLunch provided on in- office daysThis position is based in London, UK. Office post code: W1F 8WECome Work With Us!We're building a team with diverse perspectives, identities, and professional experiences. We evaluate candidates through a business lens and believe that diversity and unique viewpoints make our company stronger, more dynamic, and a great place to build a career.We've been recognized by Built In, GeekWire, Comparably, G2, Forbes, and Deloitte Technology Fast 500 for our culture, innovation, leadership, compensation, and more. At Hiya, we're a people-centric company focused on helping each employee grow both personally and professionally. We create a culture of support and empowerment that challenges the status quo, resulting in an energized team that's passionate about their work. You'll love working here if you're looking for an innovative challenge that's disrupting an industry. Come join us!

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About the teamOpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development.About the roleForward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams.You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams.This role is based in Singapore. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. 50% travel is expected.In this role you willOwn technical delivery across multiple deployments from first prototype to stable production.Build full-stack systems that deliver customer value and sharpen how we learn.Embed closely with customer teams, understand their needs, and guide adoption of what you build.Scope work, sequence delivery, and remove blockers early.Make trade-offs between scope, speed, and quality; adjust plans to protect delivery.Contribute directly in the code when progress or clarity depends on it.Codify working patterns into tools, playbooks, or building blocks that others can use.Share field feedback that helps Research and Product understand where the models succeed and where they can improve.Keep teams moving through clarity and follow-through.You might thrive in this role if youBring 5+ years of engineering or technical deployment experience that includes customer-facing work.Have scoped and delivered complex systems in fast-moving or ambiguous environments.Write and review production-grade code across frontend and backend using Python, JavaScript, or comparable stacks.Have built or deployed systems powered by LLMs or generative models and understand how model behaviour affects product experience.Simplify complexity and make fast, sound decisions under pressure.Communicate clearly with engineers, product teams, and customer stakeholders.Spot risks early and adjust without slowing down.Model calm and judgment when the stakes are high.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the teamThe AI Deployment Engineering team ensures the safe and effective deployment of Generative AI applications for developers and enterprises. We serve as trusted technical advisors, helping customers and partners move from early experimentation to production-scale AI systems.As a Partner AI Deployment Engineer focused on AWS, you will operate at the center of one of our most strategic partnerships, driving joint customer success and enabling AWS and partner ecosystems to scale adoption of OpenAI-powered solutions.About the roleWe are looking for a highly experienced technical leader to serve as the primary technical counterpart to AWS field leadership (Solutions Architects, Specialists, and Partner teams).This role goes beyond individual deal support—you will shape strategy, define engagement models, and build repeatable systems that scale across AWS globally. You will work across pre- and post-sales, guiding complex enterprise customers from ideation to production while enabling AWS and partners to independently drive deployments.You will combine deep technical expertise, strong judgment, and ecosystem leadership to maximize impact across a portfolio of high-priority opportunities.This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.In this role, you will:Strategic AWS Engagement & InfluenceServe as the senior technical counterpart to AWS field leadership, building trust and credibility across regions and teams.Influence joint account strategy and technical direction for high-priority opportunities.Shape how OpenAI engages with AWS by defining engagement models, prioritization frameworks, and best practices.Proactively identify and drive net-new opportunities and high-impact use cases across the AWS ecosystem.Complex Deal Leadership & ExecutionLead technical strategy for large, ambiguous, and high-stakes enterprise engagements.Guide customers from early ideation through architecture design, prototyping, and production deployment.Act as a technical decision-maker and escalation point, de-risking complex implementations.Apply strong judgment to prioritize opportunities and allocate limited technical resources for maximum impact.Solution Architecture & Hands-On BuildingDesign and communicate end-to-end AI architectures leveraging OpenAI and AWS services.Build and guide development of prototypes, POCs, and reference implementations to accelerate adoption.Establish best practices for scalable, secure, and production-ready GenAI systems.Ensure solutions are designed for repeatability, extensibility, and partner-led delivery.Ecosystem Enablement & ScaleEnable AWS and partners through scalable technical motions (workshops, playbooks, reference architectures, demos).Develop reusable solution patterns and assets that can be deployed independently by AWS teams and SIs.Mentor and uplift partner technical teams, accelerating their path to self-sufficiency.Scale impact by working through GSIs, RSIs, and ISVs, rather than relying solely on direct engagement.Cross-Functional Leadership & FeedbackPartner closely with Alliances, Product, Engineering, GTM, and Enablement to align on strategy and execution.Act as a bridge between field and product, delivering high-signal insights to inform roadmap and prioritization.Contribute to internal knowledge systems and help define standards, patterns, and playbooks for the ADE function. You’ll thrive in this role if you:Have 8+ years of technical consulting (or equivalent) experience, managing C-level technical and business relationships with complex global organizations.Operate as a technical leader and systems thinker, not just an individual contributor.Balance hands-on building with strategic influence and scale.Know when to go deep technically vs. enable others to execute.Build trust quickly with engineers, architects, and executives alike.Default to creating repeatable patterns, not one-off solutions.Are comfortable owning ambiguous, high-visibility problem spaces.Take a long-term, ecosystem-oriented view of impact.Are motivated by driving customer and partner success at scale.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the TeamOpenAI’s API Multicloud team sits within B2B Applications and is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS. The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied.The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including AWS-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure.About the RoleWe’re hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration.You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time.In this role, you willPartner with strategic customers and internal teams to define target model behaviors, diagnose failure modes, and translate real-world needs into training, evaluation, and system requirements.Build and scale production ML systems for model customization, post-training, and fine-tuning-as-a-service workflows.Investigate whether training and customization workflows are producing the intended outcomes, and identify changes to data, evaluation, training, or infrastructure that improve performance.Partner with backend and infrastructure engineers to integrate ML capabilities into AWS-native API environments.Feed learnings from partner deployments back into the platform by proposing and implementing improvements to post-training systems, tooling, APIs, and developer workflows.Work closely with Research and Applied teams to bring model improvements, training workflows, and evaluation best practices into production.Help design systems that allow strategic partners and enterprise customers to safely customize OpenAI models for high-value use cases.Debug and improve complex systems spanning model behavior, training data, APIs, distributed infrastructure, and customer-facing product surfaces.Operate with high ownership in a 0→1 environment where requirements are ambiguous, systems are evolving quickly, and reliability matters.Your background might look something like:Master’s or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.7+ years of professional engineering experience in relevant ML, infrastructure, or product-driven engineering roles.Strong ML engineering experience building, training, fine-tuning, evaluating, or deploying production AI systems, with hands-on experience in deep learning, transformer models, and frameworks like PyTorch or TensorFlow.Familiarity with training and fine-tuning large language models, including methods like supervised fine-tuning, distillation, preference optimization, reinforcement learning, or other post-training techniques.Strong software engineering fundamentals, including data structures, algorithms, systems design, and high-quality production code in Python, Rust, or similar languages.Experience with model customization, evaluation systems, data pipelines, distributed systems, cloud infrastructure, or production ML platform tradeoffs.Ability to operate across model behavior, APIs, and infrastructure, while collaborating closely with Research, Safety, product engineering, infrastructure, and external technical partners.Comfort moving quickly through ambiguity, owning problems end-to-end, and learning whatever is needed to get the job done.Bonus: experience with AWS, Kubernetes, agents, tool use, runtime environments, AI developer platforms, or speech models.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About the teamThe Codex Deployment Engineering team helps customers adopt OpenAI's coding tools throughout their software development lifecycle. We act as trusted technical partners, guiding engineering teams as they integrate Codex into their projects and workflows. Our customers span digital-native companies to global enterprises, and we work side-by-side to accelerate how they plan, build, and deliver software.About the RoleWe are seeking a technically deep, creativity-driven AI Deployment Engineer who is already a power user of AI coding tools and passionate about pushing the boundaries of developer productivity. You will partner directly with engineering leaders and hands-on builders to design, validate, and scale advanced AI workflows, often using Codex to prototype and build the very demos, integrations, and automations customers ultimately adopt.This is a highly cross-functional role that blends technical architecture, product strategy, and customer-facing leadership. You’ll work closely with Sales, Solutions Engineering, Product, Applied Engineering, and the broader Codex organization to advocate for customer needs, shape product direction, and accelerate the successful deployment of intelligent coding systems across some of the world’s most influential companies.In this role, you will:Serve as the primary technical subject matter expert on OpenAI Codex for a portfolio of customers, embedding deeply with them to enable their engineering teams and build coding workflows.Partner directly with customers to design and implement AI-enhanced development workflows, from rapid prototyping through scalable production rollout.Build high-quality demos, reference implementations, and workflow automations, using Codex itself as part of your development process.Lead large-format workshops, technical deep dives, and hands-on enablement sessions that help engineering organizations adopt AI coding tools effectively and safely.Contribute technical content including examples, guides, patterns, and best practices to the OpenAI Cookbook to help the broader developer community accelerate their work with Codex.Gather high-fidelity product insights from real customer deployments and translate them into clear product proposals and model feedback for internal teams.Influence customer strategy and decision-making by framing how AI coding tools fit into their SDLC, technical roadmap, and organizational workflows.Serve as a trusted advisor on solution architecture, operational readiness, model configuration, security considerations, and best-practice adoption.You’ll thrive in this role if you:Have 5+ years of technical consulting, post-sales engineering, solutions architecture, or similar experience working directly with customers.Are an active power user of AI coding tools and have deeply customized your own developer workflow; you have a point of view on what makes engineers more productive.Enjoy building scrappy, high-signal demos, integrations, and prototypes that clearly articulate what Codex can enable, often using Codex to accelerate your own development process.Have experience delivering large, high-impact workshops or technical training to engineering teams and know how to craft sessions that are engaging, hands-on, and outcomes-driven.Have contributed technical guides, patterns, or examples publicly and care about clarity, pedagogy, and community impact.Communicate complex technical concepts in clear, persuasive written and verbal form especially when helping customers make strategic decisions about where and how to apply AI.Are excited by ambiguous, rapidly evolving problem spaces and enjoy iterating toward novel solutions hand-in-hand with customers.Care about customer success, reliability, safety, and operational excellence as much as you care about technical ingenuity.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.If you'd like to build the world's best AI cloud, join us.*Note: This position requires presence in our San Jose or San Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. Information Systems at Lambda is responsible for building and scaling the internal systems that power our business. We partner across the company—Finance, GTM, Engineering, and People—to implement tools, automate workflows, and ensure data flows securely and accurately. Our scope includes enterprise applications, integrations, data platform and analytics, compliance automation, and all things IT. About the RoleWe are seeking an experienced Senior Business Systems Architect to lead and innovate across our enterprise systems landscape. This role will be pivotal in driving operational excellence through the design, implementation, and optimization of scalable business processes and systems integrations. You will collaborate with cross-functional teams to create seamless workflows across financial systems, supply chain, and customer-facing platforms while leveraging process automation tools and middleware solutions.Your responsibilities will include architecting end-to-end solutions, managing complex system integrations, and building a strategic roadmap for enterprise system enhancements. This role requires strong leadership, deep technical expertise, and a proactive approach to solving business challenges.What You’ll DoStrategic Leadership: Collaborate with stakeholders across functions to develop and execute scalable system roadmaps, aligning business goals with system capabilities.Solution Design & Implementation: Architect and deploy advanced workflows, configurations, and modules in enterprise platforms like NetSuite, Stripe, and Maxio.Tooling Selection & Standardization: Lead the evaluation, selection, and implementation of tools and systems across the business to ensure alignment with operational needs, scalability, and long-term goals. Establish standards for system usage and integration.Integration & Automation: Manage integrations and optimize iPaaS tools (e.g., Workato, Mulesoft) to ensure seamless data flow, interoperability, and automated processes across platforms.Compliance & Optimization: Ensure SOX compliance through robust internal controls, system audits, and governance while driving continuous system improvements.Support & Analytics: Troubleshoot complex issues, mentor team members, and deliver actionable insights through advanced reporting and dashboards to support decision-making.What We’re Looking For:Experience & Certification:16+ years of experience in business systems architecture or administration, including hands-on implementation of enterprise systems.Strong understanding of Finance technology stacks, including NetSuite, Billing systems and related business applicationsCertifications in relevant platforms (e.g., NetSuite Administrator, iPaaS) strongly preferred.Technical Expertise:Proficiency in languages like JavaScript/SQL/ HTML/CSS/Python.Strong experience with middleware and low/no-code platforms (e.g., Workato, Mulesoft, Alteryx) for system integrations & workflow automations.Process Automation:Demonstrated success in deploying process automation tools to streamline operations and increase efficiency.Compliance & Controls:Strong knowledge of ITGCs (IT General Controls) and SOX compliance.Leadership & Communication:Excellent communication skills to effectively collaborate across all levels of leadership—from technical staff to senior executives.Proven ability to present complex technical solutions in a clear and compelling mannerAI Automation & DevelopmentHands-on experience leveraging AI and machine learning tools to design, build, and deploy intelligent automation solutions that enhance business processes.Proficiency with AI-powered platforms and frameworks (e.g., OpenAI, Anthropic, LangChain, or similar) to develop custom workflows, copilots, and agentic solutions.Proven ability to identify high-impact automation opportunities and translate them into scalable AI-driven implementations across finance and enterprise systems.Nice to HaveProficiency in system customization tools like SuiteScript, Salesforce Flow, or equivalent.Experience with building Internal AI apps on AWS.Salary Range InformationThe annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description. About LambdaFounded in 2012, with 500+ employees, and growing fastOur investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent CoveWe have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOGOur values are publicly available: https://lambda.ai/careersWe offer generous cash & equity compensationHealth, dental, and vision coverage for you and your dependentsWellness and commuter stipends for select roles401k Plan with 2% company match (USA employees)Flexible paid time off plan that we all actually useA Final Note:You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills.Equal Opportunity EmployerLambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.