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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 involvesAs a Senior Software Engineer on the Platform - Cloud Events team, you will ensure that data captured by Hayden’s devices is properly validated and assessed by the powerful ML models that run in the Cloud. In this role you will level up our ML operations by enabling a more efficient model improvement lifecycle. You will work closely with the Product Team, the Technical Program Managers, and our partner engineering teams that build the edge software and make sense of our sensor data. We’re looking for someone who loves leveling up their team through code review, improving architecture, and thinking systemically. This position is based in San Francisco and it follows a hybrid schedule with at least 3 days in-office per week.  Key ResponsibilitiesBelow are your primary responsibilities. These represent the core areas where you’ll make an impact. As part of a rapidly evolving team, we look forward to your impact expanding over time.Maintain a high level of code quality through code review and documentationOptimize machine learning operations with robust systems and by collaborating across teamsExpand capabilities of event pipeline to satisfy both general and client specific needsReduce cost of doing business with by optimizing usage of cloud resources, especially GPUs Required QualificationsThe qualifications below outline the experience and skills most relevant to success in this role. We recognize that skills and potential come in many forms, and we welcome diverse experiences that advance our mission.Experience: 7+ years of overall experience, 2+ years building high throughput backend servicesCore Skills: Professional experience with Golang and/or Python, distributed systems thinking, ML Ops knowledge a plusPersonal Attributes: Collaborative teammate and code reviewer, detail oriented system designerEducation: BS in Computer Science or related fieldNice to Have: Professional experience with government technology, ML Operations experience, Familiarity with AWS specific implementation of managed services

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At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. This team helps automate audit readiness work while keeping customers in control. This is a rare opportunity to lead a zero-to-one build in one of the fastest-growing areas of our business, transforming Vanta into an AI-first platform.The team's mission is to make AI a core differentiator of Vanta by enabling and accelerating product innovation, and creating reliable, trustworthy, and high-quality customer experiences. The team is currently building out our Vanta Agent product, focused on downmarket and startup customers initially, with plans to scale the product to all customer segments. Core projects include agentic evidence collection, reducing manual work while ensuring the customer remains the final approver in all decisions.In this role, you'll manage a team that's scaling rapidly—currently 7 engineers with plans to grow to scale further throughout the year. You'll work closely with Vanta's AI platform team, product, and GRC subject matter experts to ship AI features that deliver magical customer experiences.Visit our Vanta Engineering Blog to learn more about what our team is working on! What you’ll do as an Engineering Manager at Vanta:Build and scale a high-performing team, hiring strategically to fill skill gaps as the team growsCoach, mentor, and create an environment where your team can do their best work and deliver for the businessSet direction and guide technical strategy for AI agent and downmarket products, ensuring long-term value aligned with Vanta's business prioritiesPartner closely with product, design, and AI platform teams to ship customer-facing AI features that automate audit work while maintaining human-in-the-loop controlsChampion best practices for applied AI, including prompt engineering, RAG, agentic frameworks, and quality evaluationNavigate rapid change and ambiguity with adaptability, iterating quickly on roadmaps as the team's charter and direction evolveHow to be successful in this role:2+ years of experience managing technical teams of 4-8+ engineersProven track record as a strong individual contributor before transitioning to management, with hands-on applied AI experienceDeep knowledge of building LLM-backed products, including experience with prompting, RAG, agent frameworks, and quality hill-climbingExperience in fast-paced, startup environments; founder background or YC experience is a strong plusStrong adaptability and comfort with ambiguity—you can quickly iterate on roadmaps without too much attachment as priorities evolveExcellent collaboration and influencing skills across engineering, product, design, and cross-functional teamsFamiliarity with Vanta's tech stack (TypeScript, React, Node.js) or willingness to ramp quicklyOpen to using AI to amplify their skills and strengthen their work - demonstrating curiosity, a willingness to learn, and sound judgment in applying AI responsibly to improve efficiency and impact.What you can expect as a Vanta’n:Industry-competitive salary and equityComprehensive medical, dental, and vision coverage, with 100% of employee-only benefit premiums covered for most medical plans16 weeks fully-paid Parental Leave for all new parentsHealth & wellness stipendRemote workspace, internet, and cellphone stipendCommuter benefits for team members who report to the SF and NYC officeFamily planning benefitsMatching 401(k) contribution with immediate vestingFlexible PTO policy, plus 80 hours of Sick Time11 company-paid holidaysVirtual team building activities, lunch and learns, and other company-wide events!Offices in SF, NYC, London, Dublin, Tel Aviv, and SydneyTo provide greater transparency to candidates, we share base pay ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar-stage growth companies. Final offer amounts are determined by multiple factors and may vary based on candidate location, skills, depth of work experience, and relevant licenses/credentials. #LI-remoteAt Vanta, we are committed to hiring diverse talent of different backgrounds and as such, it is important to us to provide an inclusive work environment for all. We do not discriminate on the basis of race, gender identity, age, religion, sexual orientation, veteran or disability status, or any other protected class. As an equal opportunity employer, we encourage and welcome people of all backgrounds to apply.About VantaWe started in 2018, in the wake of several high-profile data breaches. Online security was only becoming more important, but we knew firsthand how hard it could be for fast-growing companies to invest the time and manpower it takes to build a solid security foundation. Vanta was inspired by a vision to restore trust in internet businesses by enabling companies to improve and prove their security. From our early days automating security monitoring for compliance standards like SOC 2, HIPAA and ISO 27001 to creating the world's leading Trust Management Platform, our vision remains unchanged. Now more than ever, making security continuous—not just a point-in-time check— is essential. Thousands of companies rely on Vanta to build, maintain and demonstrate their trust— all in a way that's real-time and transparent.Referral InstructionsIf you are being referred for the role, please contact that person to apply on your behalf.   

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About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance.We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will:• Build internal apps for enterprise operations across Finance, People, and GTM• Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling• Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries• Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance• Build evals, monitoring, metrics, and regression tests for agentic workflows• Create reusable infrastructure, patterns, and components that other enterprise teams can build on• Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you:• Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs• Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling• Have experience building internal apps, backend services, APIs, workflow systems, or integration platforms• Understand enterprise systems, including controls, approvals, auditability, compliance, and permissions• Have practical AI systems experience with RAG, evals, monitoring, MCP/tool use, structured outputs, or multi-agent workflows• Have strong data architecture fundamentals, including ingestion, modeling, quality, lineage, and governance• Communicate clearly with technical stakeholders, system owners, and business owners• Take high ownership in ambiguous, cross-functional environmentsAbout 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 partners closely with customers to help them move from experimentation to production with OpenAI’s technologies. We act as trusted technical advisors, working across customer strategy, architecture, deployment, and adoption to help organizations realize meaningful impact from frontier AI.The Startups segment serves fast-moving, high-growth companies that are often building new products, workflows, and businesses directly on top of AI. These customers move quickly, operate with high ambiguity, and expect practical, creative, and technically rigorous partnership. About the RoleWe are looking for an AI Deployment Engineering Manager, Startups to lead and scale the Startups AI Deployment Engineering motion. This team helps high-growth startups move quickly from experimentation to production, unlock meaningful usage, and build durable technical partnerships with OpenAI.This leader will operate in a high-velocity customer segment where founders, CTOs, and technical teams expect speed, judgment, and hands-on problem-solving. They will balance team leadership, technical depth, customer prioritization, and cross-functional influence across Sales, Product, Engineering, Research, and broader go-to-market teams.In this role, you will define how OpenAI supports startup customers at scale: identifying where deep technical engagement can unlock outsized impact, building repeatable deployment mechanisms, and ensuring the team can serve a broad and dynamic customer base without losing quality or strategic focus. In This Role, You WillCraft and continuously refine the strategic vision and operating model for the Startups AI Deployment Engineering team, aligning it with OpenAI’s broader company objectives and the evolving needs of high-growth startup customers.Lead, mentor, and grow a team of high-performing technical ICs supporting startup customers across AI-native, developer-led, and product-led companies.Help startups move from early experimentation to production usage by identifying technical blockers, advising on architecture, and driving practical paths to deployment.Partner closely with Sales to determine where technical engagement can accelerate adoption, production usage, and long-term account growth.Represent the technical voice of startup customers by synthesizing high-signal feedback, especially around developer experience, product gaps, deployment blockers, model performance, and emerging use cases.Translate recurring startup needs into repeatable playbooks, starter packs, reference architectures, internal tooling, and customer-facing assets that help the broader team move faster.Serve as a senior technical escalation point for priority startup customers, including founder-, CTO-, and technical executive-level conversations.Balance urgent customer needs with OpenAI’s broader product and platform priorities, especially when startups request niche features, bespoke support, or accelerated roadmap changes.Coach AI Deployment Engineers on technical quality, customer judgment, prioritization, executive communication, and cross-functional partnership.Partner across Sales, Product, Engineering, Research, and other GTM teams to improve how OpenAI supports startups from early adoption through scaled production usage.You Might Thrive in This Role If YouHave proven experience founding, scaling, or operating within early-stage startups, ideally in technical leadership roles where you owned both product or customer outcomes and technical execution.Have a strong track record of building and leading technical, customer-facing teams in high-growth, ambiguous, or startup-heavy environments.Bring strong technical depth across APIs, platform products, AI/ML systems, developer workflows, and production deployment considerations.Have experience creating scalable operating models, not just managing one-off customer escalations.Are comfortable working directly with founders, CTOs, technical executives, and highly technical ICs.Demonstrate strong judgment about when to go deep for a strategic customer versus when to build repeatable mechanisms for the broader segment.Can translate complex technical and product considerations into clear decisions, practical guidance, and customer-facing recommendations.Operate with speed, iteration, and pragmatic customer impact without sacrificing quality, safety, or OpenAI’s long-term platform strategy.Are personally committed to fostering the safe and beneficial development of AI.Success in This Role May Look LikeIncreased startup account usage, including tokens, requests, and production workloads.A strong cadence of successful customer sprints and production-oriented technical engagements.High-quality customer stories, founder and CTO satisfaction, and referenceable startup wins.Creation of repeatable startup deployment patterns, starter packs, templates, and reference architectures.Strong Product and Research feedback loops informed by startup customer needs and emerging use cases.A healthy, high-performing team with strong prioritization, clear operating mechanisms, and the ability to scale coverage across a high-demand segment.    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 is responsible for ensuring the safe and effective deployment of OpenAI technologies across developers and enterprises. We act as trusted technical partners, helping customers move from experimentation to production by designing, implementing, and scaling real-world AI applications.The Codex Deployment Engineering team focuses on enabling organizations to adopt next-generation AI coding tools and intelligent automations throughout their software development lifecycle. We partner directly with engineering teams to integrate Codex into their workflows — from early experimentation and pilot design through enterprise-scale production rollout — ensuring AI-enhanced developer experiences are reliable, secure, and deeply embedded within customer environments.About the roleWe are seeking an experienced technical leader to manage a team of AI Deployment Engineers responsible for driving successful Codex adoption across strategic customers. In this role, you will lead engineers who work hands-on with customer development teams to design AI-enabled workflows, deploy production-ready solutions, and establish scalable patterns for AI-powered software development.As a manager, you will define how deployment engagements operate at scale — setting technical strategy, coaching engineers, and ensuring consistent execution across customer implementations. You will serve as both a people leader and technical advisor, partnering closely with Sales, Product, Research, and Engineering teams to translate customer needs into deployment best practices and product insights.Success in this role will be measured by production deployments, sustained developer adoption, and the creation of repeatable deployment patterns that accelerate Codex usage across organizations.This role is open in both our London and Munich office. 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:Lead, hire, and mentor a high-performing team of AI Deployment Engineers supporting Codex customers across strategic accounts.Own the operating model and engagement strategy for Codex deployment efforts, ensuring customers successfully move from pilot to production adoption.Guide teams in designing and implementing AI-enhanced development workflows, automations, and scalable deployment architectures.Act as the senior technical escalation point for complex customer implementations and deployment challenges.Partner with Sales, Product, Research, and Applied Engineering teams to align customer outcomes with product direction and roadmap priorities.Help establish repeatable deployment playbooks, technical patterns, and best practices that enable scaled adoption of AI coding tools.Coach engineers to operate as trusted advisors to engineering leadership and executive stakeholders.Synthesize insights from customer deployments and translate them into actionable feedback for internal teams.Champion safe, reliable, and effective adoption of AI-powered development workflows across industries.You might thrive in this role if you:Have 8+ years of experience in technical customer-facing roles such as deployment engineering, solutions architecture, technical consulting, or post-sales engineering.Have 2+ years of experience leading technical teams, including hiring, mentoring, and developing engineers.Have experience deploying Generative AI, developer platforms, or cloud-based software solutions into production environments.Possess hands-on technical experience with software development systems and programming languages such as Python or JavaScript.Understand modern software development lifecycles and how AI tooling transforms developer productivity and workflows.Are an effective communicator who can translate complex technical and business topics to both engineering teams and executive stakeholders.Thrive in ambiguous, fast-moving environments and enjoy building new operating models and teams from first principles.Demonstrate strong ownership, humility, and a commitment to helping both customers and teammates succeed.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 is responsible for ensuring the safe and effective deployment of OpenAI technologies across developers and enterprises. We act as trusted technical partners, helping customers move from experimentation to production by designing, implementing, and scaling real-world AI applications.The Codex Deployment Engineering team focuses on enabling organizations to adopt next-generation AI coding tools and intelligent automations throughout their software development lifecycle. We partner directly with engineering teams to integrate Codex into their workflows — from early experimentation and pilot design through enterprise-scale production rollout — ensuring AI-enhanced developer experiences are reliable, secure, and deeply embedded within customer environments.About the roleWe are seeking an experienced technical leader to manage a team of AI Deployment Engineers responsible for driving successful Codex adoption across strategic customers. In this role, you will lead engineers who work hands-on with customer development teams to design AI-enabled workflows, deploy production-ready solutions, and establish scalable patterns for AI-powered software development.As a manager, you will define how deployment engagements operate at scale — setting technical strategy, coaching engineers, and ensuring consistent execution across customer implementations. You will serve as both a people leader and technical advisor, partnering closely with Sales, Product, Research, and Engineering teams to translate customer needs into deployment best practices and product insights.Success in this role will be measured by production deployments, sustained developer adoption, and the creation of repeatable deployment patterns that accelerate Codex usage across organizations.This role is open in both our London and Munich office. 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:Lead, hire, and mentor a high-performing team of AI Deployment Engineers supporting Codex customers across strategic accounts.Own the operating model and engagement strategy for Codex deployment efforts, ensuring customers successfully move from pilot to production adoption.Guide teams in designing and implementing AI-enhanced development workflows, automations, and scalable deployment architectures.Act as the senior technical escalation point for complex customer implementations and deployment challenges.Partner with Sales, Product, Research, and Applied Engineering teams to align customer outcomes with product direction and roadmap priorities.Help establish repeatable deployment playbooks, technical patterns, and best practices that enable scaled adoption of AI coding tools.Coach engineers to operate as trusted advisors to engineering leadership and executive stakeholders.Synthesize insights from customer deployments and translate them into actionable feedback for internal teams.Champion safe, reliable, and effective adoption of AI-powered development workflows across industries.You might thrive in this role if you:Have 8+ years of experience in technical customer-facing roles such as deployment engineering, solutions architecture, technical consulting, or post-sales engineering.Have 2+ years of experience leading technical teams, including hiring, mentoring, and developing engineers.Have experience deploying Generative AI, developer platforms, or cloud-based software solutions into production environments.Possess hands-on technical experience with software development systems and programming languages such as Python or JavaScript.Understand modern software development lifecycles and how AI tooling transforms developer productivity and workflows.Are an effective communicator who can translate complex technical and business topics to both engineering teams and executive stakeholders.Thrive in ambiguous, fast-moving environments and enjoy building new operating models and teams from first principles.Demonstrate strong ownership, humility, and a commitment to helping both customers and teammates succeed.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 Francisco office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. The Field Engineering team is a group of ML engineers working hands-on with customers to optimize, deploy, and scale ML workloads on the most advanced GPU infrastructure available. We partner with enterprise, YC, and on-demand customers on some of the most demanding ML use cases in the industry and we're growing.This summer, we're looking for an ML engineering intern to embed with the team, dig into real customer optimization work, and help build the foundation that lets us scale. If you want hands-on experience at the intersection of cutting-edge ML and real-world customer impact, this is the role.What You'll DoLearn directly from ML engineers who made the transition to customer-facing field engineering, gaining firsthand exposure to how deep ML expertise translates into real-world customer impactWork on real, cutting-edge customer workloads running on the most advanced GPU infrastructure available, supporting customer onboarding, optimization engagements, and production deployments across some of the most demanding ML use cases in the industryReview prior optimization work, evaluate strategies against current best practices, and recommend improvementsDevelop a structured optimization playbook and case studies that capture the team's methodology and quantify the value of field engineering work in a repeatable, scalable formatPresent your work to company leadership at the close of the engagementYouCurrently pursuing or just completed a Master's degree in Computer Science, Machine Learning, or a related fieldStrong Python skills with hands-on experience in ML inference, model optimization, benchmarking / evaluations, or applied ML deployment.Have a solid background and general knowledge of machine learning model architectureYou have the skillset to be able to write code (without any AI assistance) to build an ML model and debug from scratch.You understand how models run in production – MLOps tools, open-source models, orchestration strategies.You have a strong understanding of fine-tuning models.Are curious and keep up to date with new models, techniques, strategies, and releases in machine learning and are driven to bring these insights to your work.Can write clearly for both technical and non-technical audiences, translating results is as important as producing themComfortable using Claude or equivalent AI tools as a core part of your daily workflowSelf-directed: given a scoped problem and a mentor, you can break it into milestones and drive it to completionNice to HaveFamiliarity with LLM inference optimization frameworks (vLLM, sgLang, Modular, TensorRT-LLM, or similar)Are able to write tests to create layer-wise benchmarking for ML model performanceFamiliarity with networking, storage, and various orchestration tools / methods.Prior internship at an ML infrastructure, cloud, or GPU hardware companyInterest in or prior exposure to customer-facing engineering, solutions engineering, or developer relationsSalary Range InformationThis is an hourly role, eligible for overtime. The hourly rate for this position has been set based on market data and other factors. However, a hourly rate 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.

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ABOUT POOLSIDEIn this decade, the world will create Artificial General Intelligence. There will only be a small number of companies who will achieve this. Their ability to stack advantages and pull ahead will define the winners. These companies will move faster than anyone else. They will attract the world's most capable talent. They will be on the forefront of applied research, engineering, infrastructure and deployment at scale. They will continue to scale their training to larger & more capable models. They will be given the right to raise large amounts of capital along their journey to enable this. They will create powerful economic engines. They will obsess over the success of their users and customers.Poolside exists to be this company: to build a world where AI will be the engine behind economically valuable work and scientific progress. We believe the fastest way to reach AGI lies in accelerating software development itself, by reshaping the developer experience with agentic systems, coding assistants, and the frontier models that power them. We deploy these systems directly into the development environments of security-conscious enterprises.ABOUT OUR TEAMWe were founded in the US and have our home there, but our team is distributed across Europe and North America. We get our fix of in-person collaboration (and croissants) in Paris each month for 3 days, always Monday-Wednesday, with an open invitation to stay the whole week. We also do longer off-sites once a year.Our team is a multidisciplinary blend of research, engineering, and business experts. What unites us is our deep care for what we build together. We’re in a race that requires hard work, intellectual curiosity, and obsession; to balance this intensity, we’ve assembled a team of low ego and kind-hearted individuals who have built the special culture Poolside has. By building collaboratively and with intention, we create a compounding effect that moves the entire company forward towards our mission: reaching AGI through intelligence systems built for software development.ABOUT THE ROLEYou’ll be working on our data team focused on the quality of the datasets being delivered for training our models. This is a hands-on role where your #1 mission would be to improve the quality of the pretraining datasets by leveraging your previous experience, intuition and training experiments. This includes synthetic data generation and data mix optimization. You’ll closely collaborate with other teams like Pretraining, Postraining, Evals, and Product to define high-quality data needs that map to missing model capabilities and downstream use cases.Staying in sync with the latest research in the fields of dataset design and pretraining is key to success in this role. You will constantly lead original research initiatives through short, time-bounded experiments while deploying highly technical engineering solutions into production. With the volumes of data to process being massive, you'll have a performant distributed data pipeline together with a large GPU cluster at your disposal.Curious about the tech? Take a deep dive into our pretraining data stack in this blogpost from our 'Model Factory' series.YOUR MISSIONTo deliver large, high-quality, and diverse datasets of natural language and source code for training Poolside models and coding agents.RESPONSIBILITIESFollow the latest research related to LLMs and data quality in particular. Be familiar with the most relevant open-source datasets and models.Design and implement complex pipelines that can generate large amounts of data while maintaining high diversity and optimizing the resources available.Closely work with other teams such as Pretraining, Posttraining, Evals and Product to ensure short feedback loops on the quality of the models delivered.Suggest, conduct and analyze data ablations or training experiments that aim to improve the quality of the datasets generated via quantitative insights.SKILLS & EXPERIENCEStrong machine learning and engineering backgroundExperience with Large Language Models (LLM), including:Understanding of transformer architectures and how LLMs learnData ablations and scaling lawsMid-training and Post-training techniquesTraining reasoning and agentic modelsExperience with evals tracking model capabilities (general knowledge, reasoning, math, coding, long-context, etc)Experience in building trillion-scale pretraining datasets, and familiarity with concepts like data curation, deduplication, data mixing, tokenization, curriculum, impact of data repetition, etc.Excellent programming skills in PythonStrong prompt engineering skillsExperience working with large-scale GPU clusters and distributed data pipelinesStrong obsession with data qualityResearch experience:Author of scientific papers on any of the topics: applied deep learning, LLMs, source code generation, etc. - is a nice to haveCan freely discuss the latest papers and descend to fine detailsIs reasonably opinionatedPROCESSIntro call with one of our Founding EngineersTechnical Interview(s) with one of our Members of EngineeringTeam fit call with the People teamFinal interview with one of our Founding EngineersBENEFITSFully remote work & flexible hours37 days/year of vacation & holidaysHealth insurance allowance for you & dependentsCompany-provided equipmentWell-being, always-be-learning & home office allowancesFrequent team get togethersDiverse & inclusive people-first culture

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Forward Deployed Engineer Aussie Engineer looking to make the move to the US? Join us and build the AI platform that's rewriting a $50B industrySalary range - $180-220k USD + Equity + Benefits + Relocation Assistance + US Sponsorship  About HaastWe're building one of the first agentic systems for enterprise legal and compliance teams that actually automates their manual work. End-to-end. Delivering 80% faster compliance reviews and 4x productivity gains.We recently closed a $12M USD Series A (Peak XV Partners, DST Global, Airtree) and are growing fast in the US; building the infrastructure that will completely re-define how enterprises think about compliance.Think Canva for design. Atlassian for projects. Haast for compliance. The ProblemCompliance is a $50B global challenge. Enterprise legal and compliance teams spend a significant amount of time manually reviewing documents against policy, spotting regulatory risk, and signing off on content before go-to-market. It's painful and it's mission-critical.We're building the infrastructure that makes this manageable at scale. You'll be working on systems that directly reduce risk and unlock productivity for some of the world's largest organisations. The RoleAs our first US based Engineer; you'll be the technical bridge between our product vision and our customers' reality. You're a full-stack engineer who thrives at the intersection of innovation and execution, building our platform while staying connected to the teams actually using it.You'll split your time between heads-down building (shipping code that matters) and being engaged with customers, understanding their pain points firsthand, iterating on features in real-time, and using that feedback to shape our product direction. You'll own end-to-end technical decisions: designing systems, shipping to production, and iterating based on direct customer interaction.This is high-autonomy work. You'll collaborate directly with our founding team, move at startup velocity, and have genuine influence over both our architecture and product roadmap.  What You'll OwnDesign, architect, and ship full-stack features that directly solve our customers compliance challengesOwn the technical relationship with key customers; implementing solutions, gathering requirements, and translating feedback into product improvementsBuild scalable services and APIs that power our LLM compliance platform while keeping the customer experience front and centerMake high-impact technical decisions quickly, knowing that you'll be accountable to both our engineering standards and our customersChallenge assumptions on "why" and "how", you'll directly influence what we build and how we build itShape our product roadmap and engineering practices as we scale from Series A to market leadership Who We're Looking ForYou've built full-stack systems at meaningful scale; you're equally comfortable architecting backend services and shipping frontend code that customers interact with dailyYou're deep on one or more of: Go, Node.js/TypeScript, or Python, and you're fluent enough across the stack to own features end-to-endYou understand APIs, distributed systems, and the tradeoffs between speed and reliability in production environmentsYou genuinely enjoy working with customers; you're not just shipping features, you want to understand the human problem you're solvingYou've shipped in fast-moving environments and understand what it takes to move quickly without breaking thingsYou're curious about how LLMs work and excited about building practical applications on top of them, not just the theory Why Join HaastCompetitive benefits: PTO, Health, Dental, Vision, 401k Real impact, day one: Your code runs inside the workflows of major global enterprises immediately. You're solving mission-critical compliance problems that directly reduce risk and unlock productivity. Forward-deployed influence: You'll spend time with customers, understanding their pain points and having direct input into product decisions. Your customer insights will shape our roadmap.Equity upside: We're building a generational company in a $50B market. You'll own a meaningful stake in that value creation and be part of the defines how Haast scales. We believe in sharing success with the people who build it.Exceptional learning velocity: You'll learn more about scaling systems, working with customers, building products, and navigating the demands of a fast-growing startup in 12 months here than most roles offer in three years.Engineering-driven culture: No red tape. We hire smart people and get out of their way. Your voice matters in how we build.Flexibility and community: Fully remote across the US or Canada.   How to ApplyWe're looking for people who've shipped things they're proud of and want to work on a problem that genuinely matters.Apply with:Your CVA brief note on this question: Tell us about a time you worked with customers to ship something they actually needed. What did it take to achieve the outcome? No closing date. We review applications on a rolling basis. At Haast, we believe bold ideas come from diverse perspectives. We're committed to building a team that reflects the world we work in. Even if you don't tick every box, we'd love to hear from you. #LI-Remote

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About HandshakeHandshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.Why join Handshake now:Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feelPartner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutionsWork together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC foundersBuild a massive, fast-growing business with billions in revenueAbout Handshake AIHuman data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.About the RoleAs a Senior Applied AI Engineer at Handshake AI Enterprise, you'll embed directly inside enterprise customer environments as part of a small, expert team. You'll learn each customer's business deeply, their workflows, their bottlenecks, where the real leverage is, and translate that understanding into production-grade AI agents that measurably change how they operate.This isn't an implementation or consulting role. You'll own the full stack: defining the solution, building and deploying agents, designing evals, and iterating until performance actually moves. Over time, you'll become a genuine domain expert in your customer's vertical and use that expertise to build AI that keeps getting better.If you've built AI that works in the real world and want to do it again at much higher stakes, with better data, closer lab relationships, and a founding team that moves fast, this is the role.What You'll DoEmbed directly with enterprise customers as part of a small deployment team, developing deep understanding of their business and workflowsDefine AI-driven solutions based on real business needs, not theoretical use casesBuild and deploy production-grade agents tailored to specific customer use cases, owning end-to-end deliveryDesign and run evals to measure agent performance; iterate and hill-climb until results moveBecome a domain expert in your customer's vertical and use that expertise to build better AI over timeWork closely with Product and Platform engineers on your team to ship cohesive, reliable solutionsEstablish engineering best practices, agent patterns, and reusable frameworks that help the team scale output without sacrificing qualitySurface insights from deployments that inform Handshake's platform and product roadmapWhat We're Looking For5-6+ years of engineering experience, with strong applied AI and backend depthReal-world experience building and shipping AI applications in production, not just fine-tuning or prototypingStrong understanding of agent architectures, evals, and how to measure and systematically improve AI performanceComfort working directly with enterprise customers in ambiguous, high-stakes environmentsStrong systems thinking, you can zoom out to the business problem and zoom in to the technical solution without losing either threadHigh ownership mentality, you care about outcomes, not just outputsStrong communication skills, you'll be in the room with senior stakeholders regularly and need to earn their trust quicklyLocation: San Francisco, CA | 5 days/week in-officeExtra CreditBackground at a company with a forward deployment or field engineering modelExperience building multi-agent systems in productionDomain expertise in a specific enterprise vertical (recruiting, finance, ops, legal, etc.)Familiarity with enterprise security requirements, VPC deployments, or on-prem configurationsHistory of building evals infrastructure or AI quality measurement toolingPerksHandshake delivers benefits that help you feel supported—and thrive at work and in life.The below benefits are for full-time US employees.🎯 Ownership: Equity in a fast-growing company💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching🍼 Family Support: Paid parental leave, fertility benefits, parental coaching💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend📚 Growth: $2,000 learning stipend, ongoing development💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days🤝 Connection: Team outings & referral bonusesExplore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.

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About HandshakeHandshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.Why join Handshake now:Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feelPartner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutionsWork together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC foundersBuild a massive, fast-growing business with billions in revenueAbout Handshake AIHuman data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.About the RoleAs an Applied AI Engineer at Handshake AI Enterprise, you'll be part of a small, expert team embedded directly inside enterprise customer environments. You'll develop a deep understanding of each customer's business, their workflows, their bottlenecks, where the real leverage is, and help translate that understanding into production-grade AI agents that measurably change how they operate.This isn't an implementation or consulting role. You'll own meaningful parts of the full stack: building and deploying agents, running evals, and iterating until performance actually moves. You'll be supported by senior teammates but expected to bring real craft and ownership to everything you touch.If you've built AI that works in the real world and want to do it at higher stakes, with better data, closer lab relationships, and a founding team that moves fast, this is the role.Location: San Francisco, CA | 5 days/week in-officeWhat You'll DoContribute to customer deployments as part of a small team, developing genuine understanding of their business and workflowsBuild and deploy production-grade agents tailored to specific customer use casesDesign and run evals to measure agent performance; iterate and hill-climb until results moveWork closely with Senior Engineers, Product, and Platform teammates to ship cohesive, reliable solutionsContribute to engineering best practices, agent patterns, and reusable frameworks as the team scalesSurface insights from deployments that inform Handshake's platform and product roadmapWhat We're Looking For2-5 years of engineering experience, with backend depth and some exposure to AI or ML systems in productionHands-on experience building and shipping software in production, you care about whether it actually worksFamiliarity with agent architectures or LLM-based systems, and curiosity to go deeperComfort with ambiguity, you don't need a perfect spec to start making progressStrong communication skills, you'll interact with customers regularly and need to represent the team wellHigh ownership mentality, you care about outcomes, not just closing ticketsExtra CreditAny experience building or shipping AI applications in productionExposure to enterprise environments or customer-facing engineering rolesFamiliarity with evals, prompt engineering, or AI quality measurementDomain knowledge in a specific enterprise vertical (recruiting, finance, ops, legal, etc.)PerksHandshake delivers benefits that help you feel supported—and thrive at work and in life.The below benefits are for full-time US employees.🎯 Ownership: Equity in a fast-growing company💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching🍼 Family Support: Paid parental leave, fertility benefits, parental coaching💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend📚 Growth: $2,000 learning stipend, ongoing development💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days🤝 Connection: Team outings & referral bonusesExplore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.

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As an AI Infrastructure Engineer at Together, you are responsible for keeping all user-facing services and production systems running smoothly. You are a blend of a pragmatic operator and a software engineer that applies sound engineering principles, operational discipline, and mature automation to our operating environments and codebase. You specialize in systems (operating systems, storage subsystems, networking), while implementing best practices for availability, reliability and scalability, with varied interests in algorithms and distributed systems. Responsibilities Participate in on-call rotation (Pagerduty) to respond to production incidents Build and run our infrastructure with Ansible, Terraform, and Kubernetes to enable scaling to a massive number of concurrent users Build monitoring systems to ensure the highest quality service for our customers Design and implement operational processes (such as deployments and upgrades) Debug production issues across all services and levels of the stack Identify improvements for the product architecture from the reliability, performance and availability perspectives Plan the growth of Together AI's infrastructure Requirements 5+ years of professional AI Infra or related experience Bachelor's degree in Computer Science or a related field or equivalent work experience Knowledge of Ansible (roles, playbooks), Terraform, and Kubernetes Proficiency in programming/scripting languages Direct experience in monitoring and observability practices Knowledge of cloud services Ability to thrive in a collaborative environment involving different stakeholders and subject matter experts About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

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As an AI Infrastructure Engineer at Together, you are responsible for keeping all user-facing services and production systems running smoothly. You are a blend of a pragmatic operator and a software engineer that applies sound engineering principles, operational discipline, and mature automation to our operating environments and codebase. You specialize in systems (operating systems, storage subsystems, networking), while implementing best practices for availability, reliability and scalability, with varied interests in algorithms and distributed systems. Responsibilities Participate in on-call rotation (Pagerduty) to respond to production incidents Build and run our infrastructure with Ansible, Terraform, and Kubernetes to enable scaling to a massive number of concurrent users Build monitoring systems to ensure the highest quality service for our customers Design and implement operational processes (such as deployments and upgrades) Debug production issues across all services and levels of the stack Identify improvements for the product architecture from the reliability, performance and availability perspectives Plan the growth of Together AI's infrastructure Requirements 5+ years of professional AI Infra or related experience Bachelor's degree in Computer Science or a related field or equivalent work experience Knowledge of Ansible (roles, playbooks), Terraform, and Kubernetes Proficiency in programming/scripting languages Direct experience in monitoring and observability practices Knowledge of cloud services Ability to thrive in a collaborative environment involving different stakeholders and subject matter experts About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

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Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation.About the RoleAt Replit, we’re building an AI-native company — and that includes how we operate internally.We’re looking for a Data Scientist, People to help us build the intelligence systems behind hiring, compensation, performance, organizational design, and workforce planning.This is not a traditional People Analytics role focused on dashboards and reporting. We want someone who can use data, AI, and automation to help the company make faster and better talent decisions at scale.You’ll work across HR, Recruiting, Finance, and Data Engineering to build models, tools, and workflows that improve how the company hires, rewards, retains, and organizes talent.You’ll report into Data Science and partner closely with the People leadership team.  In this role, you willBuild the analytical foundation to evaluate compensation competitiveness. Connect Ashby offer data, band position, acceptance rates, and market benchmarks into a live system that recommends specific adjustments.Develop predictive models and tooling that help managers and recruiters make better decisions faster. Example: a regretted attrition model that flags at-risk employees 90 days in advance and surfaces the underlying signals directly into manager 1:1 prep.Design and deploy AI agents that draft first-pass recommendations for high-stakes People decisions, including compensation, promotion, and hiring. People leaders review and adjust rather than starting from scratch.Build the recruiting analytics layer that connects sourcing channel to time-to-hire to first-year performance to tenure. Use it to reallocate recruiting spend and surface weekly insights to recruiting leadership.Analyze organizational effectiveness, including spans and layers, talent density, and hiring efficiency. Identify where the org is over-leveled, under-leveled, or structurally inefficient.Partner with Finance to move from spreadsheets to live workforce model that accounts for attrition, hiring velocity, and ramp time by function.Use LLMs and agentic workflows to analyze unstructured People data at scale, including support tickets, exit interviews, performance reviews, and engagement survey responses.Replace recurring reporting cycles with always-on agents that surface insights to leaders when they need them, not on a quarterly schedule.Support high-stakes organizational and talent decisions with rigorous analysis, including executive hiring, retention, and reorganizations. Required Skills & ExperienceMinimum 6 years of experience. Targeting Senior or Staff Data Scientist depending on demonstrated scope and impact.Experience in People Analytics, compensation analytics, or workforce analyticsStrong SQL and Python skillsExperience building predictive models and analytical frameworks for business decision-makingStrong statistical foundation, including experimentation and causal inferenceExperience working with large-scale operational or behavioral datasetsDemonstrated experience using AI and LLMs in analytics workflowsAbility to communicate complex insights clearly to executives and cross-functional partnersHigh ownership mindset and comfort operating in fast-moving environmentsAbility to handle highly sensitive organizational and compensation data with discretion Preferred QualificationsExperience at a high-growth or AI-native companyExperience building internal tools, agents, or automated workflowsFamiliarity with organizational design, compensation, or talent management conceptsExperience with modern data stack tools (dbt, BigQuery, Snowflake, etc.)Experience with People systems such as Rippling, Ashby, Lattice, or Carta Bonus PointsExperience building on ReplitExperience with NLP or unstructured text analysisInterest in the future of AI-native organizations and how AI changes the way companies operateThis is a full-time role that can be held from our Foster City, CA office. The role has an in-office requirement of Monday, Wednesday, and Friday.Full-Time Employee Benefits Include:💰 Competitive Salary & Equity💹 401(k) Program with a 4% match⚕️ Health, Dental, Vision and Life Insurance🩼 Short Term and Long Term Disability🚼 Paid Parental, Medical, Caregiver Leave🚗 Commuter Benefits📱 Monthly Wellness Stipend🧑‍💻 Autonomous Work Environment🖥 In Office Set-Up Reimbursement🏝 Flexible Time Off (FTO) + Holidays🚀 Quarterly Team Gatherings☕ In Office AmenitiesWant to learn more about what we are up to?Meet the Replit AgentReplit: Make an app for thatReplit BlogAmjad TED TalkInterviewing + Culture at ReplitOperating PrinciplesReasons not to work at ReplitTo achieve our mission of making programming more accessible around the world, we need our team to be representative of the world. We welcome your unique perspective and experiences in shaping this product. We encourage people from all kinds of backgrounds to apply, including and especially candidates from underrepresented and non-traditional backgrounds.

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About Arize AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence. We’re a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Booking.com, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.The Opportunity We’re looking for an Application Engineer who thrives on solving hard problems with code. In this role, you'll have the opportunity to work at the cutting edge of generative AI in a high-impact role with autonomy and ownership. While we are a remote-first company, the nature of this role requires candidates to be based in the Buenos Aires area. What You’ll Do Debug and fix issues in our platform (and ship PRs with your fixes). Build internal tools and copilots powered by generative AI to supercharge our team. Rapidly prototype proof-of-concepts for customer use cases. Work across Engineering, Product, and Solutions to unblock customers and push the boundaries of AI adoption. What We’re Looking For You have 2-5 years of experience in software. Strong in Python and Golang; comfortable shipping fixes in production systems. Hands-on with generative AI (LLM APIs, frameworks, building copilots or automations) Hands-on with OpenTelemetry and deep familiarity with distributed tracing concepts. Familiarity with AI frameworks (CrewAI, Langchain, Langgraph, DiFy, LiteLLM, etc). Familiarity or eagerness to learn JavaScript/TypeScript. Great debugger, creative problem solver, and fast learner. Independent and resourceful. You create solutions, not dependencies. Bonus Points (but not required!) Experience in a customer-facing role Built copilots, plugins, or custom GenAI-powered applications. Open-sourced or contributed PRs to real codebases. Startup or fast-moving environment experience. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes unlimited paid time off, generous parental leave plan, and others for mental and wellness support.More About Arize Arize’s mission is to make the world’s AI work—and work for people. Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge—understanding whether AI is performing and how to improve it at scale. Learn more about what we're doing here: https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/ https://arize.com/blog/arize-ai-raises-70m-series-c-to-build-the-gold-standard-for-ai-evaluation-observability/ Diversity & Inclusion @ Arize Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI Culturally conscious events such as LGBTQ trivia during pride month We have an active Lady Arizers subgroup

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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’re pushing the envelope of AI utilization in enterprise. This requires creative researchers who don’t just want to drive incremental improvements on benchmarks or optimize an existing process but instead are looking to creatively redefine how software is used.Our researchers come from many academic backgrounds but have strong research track records, operate in an AI-native way, and would be bored staying on the rails of a traditional research org. Key ResponsibilitiesThe Multi-Agent Systems team focuses on designing architectures in which multiple agents coordinate to solve problems that require structured interaction across multiple reasoning processes. Researchers build systems that structure communication, route information, and coordinate decision-making across agents operating with different views of the problemResearchers in Multi-Agent Systems investigate the interaction patterns that govern how agents collaborate. They study how agents exchange information, critique and refine each other’s reasoning, and coordinate execution across complex workflows. Their work identifies the mechanics behind effective communication, delegation, and coordination, in effect establishing the design language for how systems of agents can operate as cohesive, high-performing teams, with capabilities that arise from interaction rather than individual performance. What We RequireBuilt or studied systems where multiple agents collaborate through structured communication, delegation, critique, or iterative coordination.Experience with agent orchestration, communication protocols, evaluator agents, or systems where multiple agents interact to exchange information, critique reasoning, and coordinate decisions over timeExperience with research in related fields, such as multi-agent reinforcement learning (MARL), graph neural networks (GNNs), knowledge graphs, mixed-initiative planning, etc.Excited about making foundational advancements in how agents coordinate, reason and collaborateProven Track Record of Research Results: Whether you’ve published in top journals, posted amazing work on twitter, or somewhere else we want to see what you've done.Uses AI Every Day: Before you can revolutionize someone else’s workflow, you need to revolutionize yours. You should be using tools like ChatGPT, Cursor, and Perplexity to accelerate your workflow.Strong Programming and Data Analysis Skills: While you might not consider yourself a software engineer you need to be able to build prototypes of your ideas and then perform the experiments to prove the effectiveness to a F500 Head of AI.Biases Towards Showing vs Telling: Our customers want to see the power of AI today vs discuss the most elegant idea that will take 5 years to realize. 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 believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.

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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 Francisco, San Jose, or Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday. About the RoleLambda is building the AI Cloud of the future. We are seeking a Staff Engineer to help our development of our Managed Kubernetes platform. Think GKE, but purpose-built for AI workloads and running on bare metal. This is a foundational technical leadership role where you will shape the infrastructure that powers the next generation of AI training and inference at scale.As a Staff Engineer on our Orchestration team, you will collaborate to help drive the technical vision for Lambda's managed orchestration services, including Managed Kubernetes, Managed Slurm on Kubernetes, and higher-level platform services for inference and AIOps. You'll work at the intersection of distributed systems, GPU-accelerated computing, and Cloud Native infrastructure to build systems that are reliable, performant, and elegantly simple for our customers.This is not a role for someone who just operates Kubernetes; it is a technical leadership role for an engineer who has synthesized the core domains of infrastructure (compute, network, storage, security) and can design holistic solutions across all of them. You'll be working closely with NVIDIA's open-source ecosystem, and partnering with internal teams across the stack to deliver a world-class managed platform. What You'll Do:Product EngineeringDrive technical vision for Lambda's Managed Kubernetes bare-metal platform, including control plane scalability, multi-tenancy, cluster lifecycle management, and high availabilityIntegrate and extend NVIDIA's open-source ecosystem: GPU Operator, Network Operator, DCGM, NCCL, and emerging projects like AICR and Topograph for topology-aware scheduling and placementDesign GPU-aware orchestration systemsLead development of services that power our managed servicesInform on and help with networking solutions for AI workloads: CNI integration (Cilium, Multus), high-performance fabrics (InfiniBand, RoCE), RDMA, and GPUDirect. You will work closely with our Network team to define and drive requirementsInform and help with storage architecture requirements for AI workloads. You will partner with Storage teams on what managed K8s, Slurm, and future services needBuild the foundation for Managed Slurm on Kubernetes, enabling traditional HPC workloads to run seamlessly alongside Kubernetes workloadDesign higher-level platform services for inference, including model serving infrastructure, autoscaling based on inference load, and multi-model deployment patternsDesign self-healing systems and automation for incident response, root cause analysis, and platform resilienceLead chaos engineering efforts to validate system behavior under failure conditions at scaleEstablish operational excellence for a managed service: upgrade automation, security patching, and zero-downtime maintenanceCross-Functional Infrastructure LeadershipServe as the technical bridge between Orchestration and other infrastructure teams (Network, Storage, Security), translating platform requirements into actionable specificationsDrive infrastructure-wide decisions that enable successful managed services. You’re someone who understands what's needed end-to-end, not just at the Kubernetes layer.Provide input on bare-metal provisioning, network topology, and storage systems to ensure they meet the needs of managed the services being built by the Orchestration organizationChampion consistency and standardization across Lambda's infrastructure stackWork directly with customers and internal teams to understand existing deployments and chart a path to the managed platformTechnical LeadershipSet technical direction for Kubernetes services across the Orchestration team, influencing roadmap and prioritizationDrive reviews and design sessions, ensuring we build systems that are scalable, maintainable, and aligned with customer needsMentor and grow engineers, establishing best practices for Kubernetes development, distributed systems, and Cloud Native engineeringCollaborate cross-functionally with Network, Storage, Security, and Customer Success teamsEngage with NVIDIA and the open-source community to stay current on GPU orchestration technologies and contribute back where appropriateRepresent Lambda externally through technical blog posts, conference talks, and strategic customer engagementsShape our AIOps vision: design intelligent systems for automated capacity planning, anomaly detection, and predictive maintenance of cloud infrastructureWho You AreYou are a creative, innovative engineer who operates at high velocity. You don't just solve problems. You find elegant solutions and ship them quickly. You embrace modern tools and AI-assisted development (like Claude Code) to accelerate your productivity and multiply your impact. You're energized by building new things, not maintaining the status quo.Required Qualifications10+ years of experience in software engineering, platform engineering, or SRE, with at least 5 years focused on Kubernetes at scaleExpert-level understanding of Kubernetes internals: API machinery, controllers, schedulers, operators, CRDs, CSI, CNI, and the extension patterns that make Kubernetes powerfulHolistic infrastructure expertise: you've synthesized knowledge across compute, networking, storage, and security, not just Kubernetes in isolation. You can build solutions that span the full stack.Strong software engineering skills in Go (required) and Python; you write production-quality code, not just scriptsDeep experience with GPU orchestration in Kubernetes: NVIDIA GPU Operator, device plugins, DCGM, MIG, time-slicing, and GPU-aware scheduling. Familiarity with NVIDIA Network Operator and GPUDirect is strongly preferred.Proven track record of technical leadership: driving design decisions across teams, mentoring engineers, and influencing infrastructure direction beyond your immediate scopeDeep experience designing and operating managed services or multi-tenant platforms. You understand what it takes to run infrastructure for external customersStrong understanding of distributed systems principles: consensus, fault tolerance, consistency models, and graceful degradationExperience with observability at scale: Prometheus, Grafana, distributed tracing, and building actionable alerting systemsSolid knowledge of Linux systems and networking (L2-L7), including high-performance networking concepts (RDMA, InfiniBand, RoCE)Experience with infrastructure-as-code and GitOps workflowsPreferred QualificationsExperience building and operating managed Kubernetes services (GKE, EKS, AKS, or similar) or working on Kubernetes control plane componentsHands-on experience with NVIDIA's open-source ecosystem beyond GPU Operator: Network Operator, NCCL tuning, Topograph, AICR, or similar emerging projectsFamiliarity with HPC and traditional job schedulers (Slurm) and Kubernetes-native batch scheduling (KAI, Volcano, Kueue)Background in confidential computingExperience migrating customers or workloads from legacy/bespoke infrastructure to standardized platformsContributions to CNCF projects, Kubernetes SIGs, or NVIDIA open-source projectsFamiliarity with security and compliance in multi-tenant environments: RBAC, Pod Security Standards, network policies, workload isolationBackground in ML infrastructure: training clusters, inference serving, simulationWhy LambdaLambda is building the essential infrastructure for the AI era. We're not just another cloud provider: we're a company founded by ML practitioners, for ML practitioners. Our customers include leading AI research labs and enterprises pushing the boundaries of what's possible with artificial intelligence.What makes this role special:You'll be building core platform services the world’s largest AI companies will consumeNVIDIA partnership: Deep integration with NVIDIA's GPU and networking stack, working with cutting-edge open-source toolingReal technical challenges: Massive scale GPU clusters and the unique demands of AI workloadsCross-stack influence: Shape not just Kubernetes, but the network, storage, and compute infrastructure that supports itDirect impact: Your work enables AI breakthroughs. Every model trained on Lambda benefits from systems you buildWorld-class team: Work alongside engineers with deep expertise in ML, systems, and infrastructureSalary 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.

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About NiviiEn Nivii.ai estamos construyendo una nueva forma de trabajar con datos. En lugar de dashboards y BI tradicional, estamos creando una AI-powered platform que permite hacer preguntas complejas en lenguaje natural y obtener respuestas estructuradas, explicables y accionables.Durante el último año pasamos de concepto a producción: hoy contamos con un sistema multi-agent que ya se utiliza en flujos reales de toma de decisiones. Ahora buscamos sumar un/a Software Engineer, AI/LLM Platform para ayudarnos a escalar, robustecer y evolucionar los sistemas core que hacen funcionar la plataforma.Sobre el rolEste rol es software-engineering-first, con AI y LLM como building blocks centrales. Vas a trabajar muy cerca del producto y de los founders, con ownership end-to-end sobre partes críticas del sistema.Lo que harásDiseñar, construir y operar servicios core de la platforma que soportan nuestros flujos de AI/LLMDesarrollar y correr sistemas LLM-based (por ejemplo text-to-SQL, reasoning agents, planners), con foco en confiabilidad, performance y costosConstruir y mantener servicios backend y APIs que orquestan pipelines complejos y multi-stepTrabajar hands-on con infra basada en Kubernetes, incluyendo deployments, scaling y debugging en producciónContribuir a workflows de DevOps y MLOps: CI/CD, environments, monitoring, logging y buenas prácticas operativasParticipar en decisiones de arquitectura alrededor de observabilidad, failure handling, evaluación y trade-offs del sistemaColaborar de forma directa con founders y producto para transformar problemas reales de negocio en soluciones técnicas robustasLo que buscamos4+ años de experiencia como software engineer en backend, ML o sistemas data-intensiveFuerte software engineering mindset, con experiencia comprobable llevando sistemas a producción y manteniéndolos en el tiempoMuy buen manejo de Python y experiencia construyendo backend services (FastAPI o similar)Experiencia práctica con Docker y Kubernetes en entornos realesConocimientos básicos a sólidos de DevOps: CI/CD, cloud environments, logging, monitoring y deploymentsExperiencia trabajando con cloud platforms (AWS preferido)Experiencia práctica con LLMs en contextos aplicados (text-to-SQL, RAG, agent-based systems, etc.)Capacidad para razonar y manejar trade-offs (calidad vs latencia, costo vs performance, simplicidad vs flexibilidad)Buen nivel de comunicación en inglésPuntos extraExperiencia con dbs de SQL, data platforms o vector dbsExperiencia diseñando frameworks de evaluación para ML o LLM systemsExperiencia previa en early-stage startups o equipos de alto ownershipLo que ofrecemosTrabajar en una plataforma AI/LLM real en producción, no demos ni research projectsAlto nivel de ownership e impacto directo en el core tecnológico y el productoEquity + salario competitivoCamino de crecimiento acelerado hacia roles senior o de liderazgo a medida que el equipo escalaModalidad híbrida en Buenos AiresInformación rápidaLocation:Buenos Aires (Híbrido)Experience:4+ añosDepartment:Engineering¿Listo para postularte?Únete a nuestro equipo y ayuda a construir el futuro de la inteligencia empresarial potenciada por IA.

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About ClayOur mission is to help organizations turn any growth idea into reality.We see growth as a creative practice, not a formula. Finding and reaching your best-fit customers takes unique ideas and constant iteration. As AI makes execution faster and tactics easier to copy, creativity is the only lasting advantage. We're already helping thousands of customers — including Anthropic, Notion, Google, and Ramp — go to market with unique data, signals, and AI research.In 2025, we raised a $100M Series C backed by world-class investors including Sequoia, CapitalG, and First Round — and crossed $100M in revenue.In 2026, we announced our second employee tender offer in 9 months at a new $5B valuation. We also launched a community equity round, for our customers, agency partners, and club members.Some things to know about us:Our community includes 11,000+ customers, 150+ integration partners, 125+ agencies, 50+ Clay clubs, and 30k members on Slack.Our culture is unique inside and outside of work. Our team members are also DJs, activists, writers, clowns, marathoners, skydivers, psychedelic therapists, social workers, and more.All employees can work for free with world-class coaches who specialize in creativity, management, and more.Our operating principles — including negative maintenance and non-attached action — guide our work. Read more about them here.Read about us in the NYT, Forbes, First Round Review, and more.Hear from our employees directly on our Glassdoor page!We're looking for someone to focus on elevating our core sale workflows; building automations and AI-systems that help us acquire new customers and kickoff successful customer journeys. Strong candidates will be builders who with a strong understanding of modern selling motions. You will operate with high agency but ground yourself in what your stakeholders need to be successful.What You'll DoBuild and own core sales workflow automations like book carving, ROE automation, signal detection, pipeline automation and morePartner closely with our Head of Sales and sales leadership to translate business needs into automation requirements and iterate based on feedbackBuild tooling that surfaces the right customer context for GSMs at the right moment; before QBRs, during renewals, and ahead of expansion conversationsPush the limits of Clay and extend our platform into new use cases, feed our product team innovative ideas, dogfood new features and ; act as a practitioner evangelist of Clay infrastructure and GTM EngineeringPartner deeply with GTM leaders and frontline teams to understand how our revenue motion works today and where it breaksOwn projects end-to-end, from discovery and prototyping through rollout, adoption, and iteration; identify opportunities to automate, augment, or redesign workflows using AI, data, and better systems designDesign systems that improve speed, visibility, data quality, and execution across the funnel; connect systems through APIs, webhooks, integrations, and automation layers so information moves cleanly across the stackMeasure performance, adoption, and business impact of what you build, then improve it over timeAct as an internal thought partner on the future of AI-native GTM systemsWhat You'll BringAt least 6-10 years working in a combination of RevOps, GTM Engineering or other similar applied technical discipline withAt least 3 years in RevOps/Sales Ops or GTM Engineering or equivalentExperience building, developing or connecting core systems like Salesforce and adjacent GTM systems including hands on experience with sales toolingProven ability to build and problem solve with methods incorporating Python, JavaScript, SQL, or TypeScript; we pull our own data on this teamTrack record of deploying and building AI-powered internal tools, automations, or agentic workflowsExperience using data warehouses, BI tools, or event-driven systemsExecutive presence -- you communicate concisely and confidently even about technical topics with non technical people while simultaneously communicating business requirements to technical audiencesProven ability to operate effectively in ambiguous and fluid hypergrowth environments -- you not only embrace change bur drive itExperience building in Clay as a primary workflow or enrichment layer is not required but is highly preferred (successful candidates with no experience in Clay will show increasing proficiency throughout the interview process)Bonus points for experience in analytics engineering, data science and /or programming languages

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Senior AI Engineer – RAG Systems Bright.AI is a high-growth Physical AI company transforming how businesses interact with the physical world through intelligent automation. Our AI platform processes visual, spatial, and temporal data from billions of real-world events—captured across edge devices, mobile sensors, and cloud infrastructure—to enable intelligent decision-making at scale. We are now hiring a Senior AI Engineer – LLM, RAG to lead the development of Retrieval-Augmented Generation (RAG) systems that harness the power of large language models (LLMs) and real-world knowledge sources. This role is pivotal to building next-generation intelligent assistants that help technicians and operators troubleshoot complex issues in industrial settings. You’ll work at the intersection of NLP, foundational models, and real-time information systems—developing intelligent tools that turn manuals, technician notes, and sensor data into actionable, conversational guidance for the physical world. Responsibilities Lead the architecture and development of RAG systems that combine LLMs (e.g., LLAMA, Mistral, Claude, GPT) with structured and unstructured external information sources. Develop AI-powered assistants to support technicians in diagnosing and resolving anomalies or failures in factory, plant, or industrial settings. Build pipelines to ingest, preprocess, and index large corpora of documents (manuals, logs, notes, procedures) for semantic search and grounding. Customize and fine-tune foundational models to incorporate domain-specific language, tone, and logic for industrial troubleshooting scenarios. Collaborate with product, data, and cloud teams to design scalable, privacy-compliant, and latency-sensitive LLM applications. Design evaluation strategies to measure performance, accuracy, and user experience of RAG-enabled systems in production settings. Stay up to date with the latest advances in LLM architectures, retrieval methods, and prompt engineering, and integrate emerging techniques into the product roadmap. Educational Background M.S. or Ph.D. in Computer Science, AI, Machine Learning, or a related field, with specialization in NLP or deep learning. Strong research or applied background in large language models (LLMs) and retrieval-augmented generation (RAG) systems. Agentic RAG experience is highly desirable. Required Skills & Expertise 5+ years of experience in machine learning or AI with a strong focus on NLP, LLMs, or conversational AI. Fluency with modern LLMs and open-source foundational models (e.g., LLAMA, Falcon, Mistral, GPT, Claude). Experience building RAG pipelines with tools like LangChain, LlamaIndex, or custom vector database integrations, with at least one production grade system was built. Fluency with prompt engineering, instruction tuning, or fine-tuning open-source models. Deep understanding of document retrieval (semantic search, embedding generation, similarity metrics) and vector stores (e.g., FAISS, Weaviate, Pinecone). Strong foundation in core machine learning techniques, including experience with reinforcement learning (RL) or decision-making models. Proficiency with ML development frameworks such as PyTorch, Hugging Face Transformers, or similar.  Strong Python programming is a must. Experience integrating AI systems into real-world applications with user-facing interfaces and operational constraints. Excellent problem-solving and critical thinking skills; ability to design solutions for complex, ambiguous problems. Strong written and verbal communication skills, with ability to collaborate cross-functionally with engineers, product managers, and domain experts. Bonus Qualifications Experience applying LLMs in industrial or physical infrastructure settings (e.g., manufacturing, logistics, utilities, energy). Knowledge of industrial control systems, maintenance workflows, or technician support processes. Exposure to multimodal models or integrating textual data with sensor and/or time-series data. Prior experience in a startup or a fast-paced environment building LLM-powered products from the ground up.