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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 the teamThe AI Deployment Engineering team works closely with frontier startups. We are trusted advisors to, and thought partners with, startups to ensure that OpenAI’s technology is deployed safely and effectively, whilst also partnering with engineering, research, and product to turn those insights into evaluation systems, product improvements, and better model behavior.This team sits at the intersection of customer reality and model quality. We combine hands-on technical depth with strong product judgment, helping translate complex, high-value use cases into clear signals that can improve both the customer experience and the underlying systems.About the roleWe are seeking a technically proficient, product-minded engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, helping them optimize their own systems and turning those learnings into durable improvements across OpenAI’s research and products. You will partner deeply on complex workflows, identify the gaps that matter, and help transform those gaps into reproducible evaluations, technical insights - helping shape OpenAI's research and product direction.This role is well suited to engineers who are equally comfortable debugging a workflow, iterating on prompts or agents, designing evaluations, and collaborating across research and product. You should be excited by ambiguous, high-impact problems and motivated by the opportunity to shape how advanced AI systems improve in practice.This role is based in our Sydney 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:Work directly with strategic startup customers to understand critical workflows, uncover failure modes, and identify high-impact opportunities for improvement.Prototype and iterate on prompts, agents, and workflow designs to better understand system behavior and unlock customer value.Synthesize and deliver valuable feedback to the Product and Research teams, turning real usage patterns into clear, reproducible evals, benchmarks, and technical artifacts that improve model and product quality and ensure customer-grounded learnings influence roadmap and model development.Build repeatable tools, patterns, and evaluation approaches that raise the quality bar across multiple use cases.Operate with strong judgment in ambiguous environments, balancing immediate technical problem-solving with longer-term system improvement.Build relationships within the startup ecosystem, serving as a technical partner to both individual customers and the broader community.You’ll thrive in this role if you:Have strong software engineering & AI fundamentals. For example, experience as a software engineer, ML engineer, Data Scientist or equivalent. Experience shipping production systems end-to-end is a strong plus.Have familiarity with, or interest in, model training pipelines and reinforcement learning.Have experience building AI applications, agents, or evaluation systems, and can reason clearly about model behavior in complex workflows.Are comfortable working directly with highly technical users and translating their challenges into concrete technical signals.Can move fluidly between prototyping, debugging, evaluation design, and cross-functional collaboration.Communicate clearly across technical and non-technical audiences.Bring high agency, strong product sense, and a bias toward building durable improvements rather than one-off fixes.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 TeamWe’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance.This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack.About the RoleWe’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident.A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT).You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack.This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most performance-sensitive inference platforms in the world.In this role, you will:Improve systems that ensure inference engine releases are correct, performant, and regression-free by evolving tooling and infrastructure for deploy gate validationBring rigor to release, validation, branching, and deployment processes across the inference stackImprove canary, async, and large-scale validation workflows for inference systemsHarden CI, testing, and validation infrastructure so failures are actionable and trustworthyReduce noisy or flaky failures caused by infrastructure instability, GPU scheduling, or test environment issuesBuild automation for failure triage, ownership detection, debugging, and escalationPartner closely with inference teams, research developer productivity, engine acceleration, and infrastructure teams to improve release quality and rollout safetyReduce developer friction in testing, debugging, and release workflows so engineers can move faster with confidenceYou might thrive in this role if:You have strong experience with CI/CD systems, testing infrastructure, release tooling, developer productivity, or large-scale build and validation systemsYou are excited by high-impact infrastructure where small regressions in correctness, latency, or reliability meaningfully affect production systemsYou care about building systems engineers can trust, not just systems that technically functionYou have strong developer empathy and enjoy improving workflows, reducing friction, and making engineers more effectiveYou demonstrate high ownership and proactively identify problems, drive improvements, and follow issues through resolutionYou are comfortable working in Python-heavy environments and debugging complex distributed systemsYou enjoy building automation that reduces manual triage, improves signal quality, and scales operational effectivenessYou are comfortable operating in ambiguous areas without a fully predefined roadmapYou enjoy partnering closely with engineers to understand workflows, pain points, and operational challengesYou are pragmatic, collaborative, and motivated by helping teams move faster with more confidenceYou are excited to learn about large-scale inference systems, even if you have not worked directly on inference beforePython experience is highly relevant, as much of the current deploy gate and validation infrastructure is Python-based. C++ experience is helpful, especially for working near inference engine code, CI build issues, or performance-sensitive systems, but it is not required.Prior inference experience is not required. The ideal candidate is someone with strong instincts around developer productivity, testing, release engineering, and automation who is excited to apply those skills in a deeply impactful inference environment. We’re looking for someone who is technically curious, comfortable navigating ambiguous, cross-functional operational problems, and is motivated to improve the reliability, safety, and developer experience of large-scale production infrastructure.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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Building Open Superintelligence InfrastructurePrime Intellect is building the open superintelligence stack - from frontier agentic models to the infra that enables anyone to create, train, and deploy them. We aggregate and orchestrate global compute into a single control plane and pair it with the full rl post-training stack: environments, secure sandboxes, verifiable evals, and our async RL trainer. We enable researchers, startups and enterprises to run end-to-end reinforcement learning at frontier scale, adapting models to real tools, workflows, and deployment contexts.We recently raised $15mm in funding (total of $20mm raised) led by Founders Fund, with participation from Menlo Ventures and prominent angels including Andrej Karpathy (Eureka AI, Tesla, OpenAI), Tri Dao (Chief Scientific Officer of Together AI), Dylan Patel (SemiAnalysis), Clem Delangue (Huggingface), Emad Mostaque (Stability AI) and many others.Role ImpactThis is a hybrid role spanning both our infrastructure layers and developer platform. You'll work on two key areas:The underlying sandbox infrastructure that powers our training systemsOur developer-facing platform for AI workload managementYou will work on a distributed system with performance engineering at its core. The role will draw on the full breadth of your systems skills, from deep Linux kernel topics to high-level distributed system design. Expect your low-level systems fortitude to be pushed as you build infrastructure that remains fast, robust, and reliable at scale.Core Technical ResponsibilitiesInfrastructure DevelopmentDesign and implement distributed orchestration infrastructure in Go and RustBuild high-performance networking and coordination componentsCreate infrastructure automation pipelines with AnsibleManage cloud resources and container orchestrationImplement scheduling systems for heterogeneous hardware (CPU, GPU, TPU)Platform DevelopmentBuild intuitive web interfaces for AI workload management and monitoringDevelop REST APIs and backend services in PythonCreate real-time monitoring and debugging toolsImplement user-facing features for resource management and job controlTechnical RequirementsInfrastructure SkillsSystems programming experience with RustStrong Linux systems knowledge, including networking, namespacing, and performance tuningVirtualization experience, including VMs, hypervisors, and low-level resource managementInfrastructure automation (Ansible, Terraform)Container orchestration (Kubernetes)Cloud platform expertise (GCP preferred)Observability tools (Prometheus, Grafana)Platform SkillsStrong Python backend development (FastAPI, async)Modern frontend development (TypeScript, React/Next.js, Tailwind)Experience building developer tools and dashboardsRESTful API design and implementationNice to HaveExperience with GPU computing and ML infrastructureKnowledge of AI/ML model architecture and trainingHigh-performance networking implementationOpen-source infrastructure contributionsWebSocket/real-time systems experienceWhat We OfferCash Compensation Range of $150-300k with significant equity incentivesFlexible work arrangement (San Francisco office preferred, remote possible for exceptional candidates)Full visa sponsorship and relocation supportProfessional development budget for courses and conferencesRegular team off-sites and conference attendanceOpportunity to shape the future of decentralized AI developmentGrowth OpportunityYou'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.We value potential over perfection - if you're passionate about democratizing AI development and have experience in either platform or infrastructure development (ideally both), we want to talk to you.Ready to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone.

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About HandshakeHandshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.Why join Handshake now:Shape how every career evolves in the AI economy, at global scale, with impact your friends, family & peers can see & feelWork hand-in-hand with world-class AI labs, Fortune 500 partners & the world's top educational institutionsJoin a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, & Palantir, among othersBuild a massive, fast-growing business with billions in revenueThe RoleHandshake is building the infrastructure layer that powers the next generation of AI agents across our platform. As a Senior Software Engineer on our Agentic Infrastructure team, you'll be at forefront of AI at Handshake, will architect & build the foundational systems that allow AI agents to plan, execute, & operate autonomously at scale. This is a rare greenfield opportunity to define how an AI-first company builds for the agentic era — at the intersection of infrastructure, AI, & direct product impact.Architect & build the core agent orchestration layer — including tool use, memory, & multi-step reasoning systems — that powers AI-driven features for 20M+ users & 1M+ employers across Handshake's platformDesign evaluation, observability, & reliability frameworks that ensure agent behavior is safe, auditable, & production-ready at scaleEstablish engineering standards for agentic development across Handshake's platform teams, enabling every engineer to build with AIPartner with ML, product, & platform engineers to ship agent-powered features from infrastructure to production at Olympic paceYou HaveMust-Haves:2-4 years of backend engineering experience, with strong proficiency in NodeJS, Typescript, &/or PythonExperience designing & operating distributed systems at significant scale for developer experienceHands-on experience building with LLM orchestration frameworks (LangChain, LlamaIndex, or similar)Deep understanding of agent architectures: tool use, multi-step reasoning, memory management, & evaluationExperience with cloud infrastructure (AWS, GCP, or Azure) & infrastructure-as-code tools like TerraformExperience with Node, JavaScript, CICD, DockerA track record of shipping production systems with high reliability, low latency, & strong observabilityStrong communication skills & ability to drive alignment across engineering & cross-functional partnersBonus Points:Open-source contributions to LLM or agent frameworksPrior experience at an AI-native company or on a dedicated AI platform teamWe OfferHandshake 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, & vision, mental health support, $500 wellness stipend📚 Growth: $2,000 learning stipend, ongoing development💻 Remote & Office: Internet, commuting, & free lunch/gym in our SF office🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days🤝 Connection: Team outings & referral bonusesExplore our mission, values, & comprehensive US benefits at joinhandshake.com/careers.

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About HandshakeHandshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.Why join Handshake now:Shape how every career evolves in the AI economy, at global scale, with impact your friends, family & peers can see & feelWork hand-in-hand with world-class AI labs, Fortune 500 partners & the world's top educational institutionsJoin a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, & Palantir, among othersBuild a massive, fast-growing business with billions in revenueThe RoleHandshake is building the infrastructure layer that powers the next generation of AI agents across our platform. As a Senior Software Engineer on our Agentic Infrastructure team, you'll be at forefront of AI at Handshake, will architect & build the foundational systems that allow AI agents to plan, execute, & operate autonomously at scale. This is a rare greenfield opportunity to define how an AI-first company builds for the agentic era — at the intersection of infrastructure, AI, & direct product impact.Architect & build the core agent orchestration layer — including tool use, memory, & multi-step reasoning systems — that powers AI-driven features for 20M+ users & 1M+ employers across Handshake's platformDesign evaluation, observability, & reliability frameworks that ensure agent behavior is safe, auditable, & production-ready at scaleEstablish engineering standards for agentic development across Handshake's platform teams, enabling every engineer to build with AIPartner with ML, product, & platform engineers to ship agent-powered features from infrastructure to production at Olympic paceYou HaveMust-Haves:4-7 years of backend engineering experience, with strong proficiency in NodeJS, Typescript, &/or PythonExperience designing & operating distributed systems at significant scale for developer experienceHands-on experience building with LLM orchestration frameworks (LangChain, LlamaIndex, or similar)Deep understanding of agent architectures: tool use, multi-step reasoning, memory management, & evaluationExperience with cloud infrastructure (AWS, GCP, or Azure) & infrastructure-as-code tools like TerraformExperience with Node, JavaScript, CICD, DockerA track record of shipping production systems with high reliability, low latency, & strong observabilityStrong communication skills & ability to drive alignment across engineering & cross-functional partnersBonus Points:Open-source contributions to LLM or agent frameworksPrior experience at an AI-native company or on a dedicated AI platform teamWe OfferHandshake 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, & vision, mental health support, $500 wellness stipend📚 Growth: $2,000 learning stipend, ongoing development💻 Remote & Office: Internet, commuting, & free lunch/gym in our SF office🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days🤝 Connection: Team outings & referral bonusesExplore our mission, values, & comprehensive US benefits at joinhandshake.com/careers.

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About the TeamOpenAI’s Forward Deployed Engineering team partners with leading semiconductor companies to deploy production-grade AI systems across the entire chip design lifecycle: design, verification, and physical design. We operate at the intersection of customer delivery and core platform development, embedding deeply with customers to translate frontier model capabilities into systems that materially reduce design cycles, improve verification quality, and accelerate innovation.Our work turns early, high-touch deployments into reusable solution patterns, evaluation practices, and technical playbooks that scale across the semiconductor ecosystem.About the RoleWe are seeking an experienced Design Verification Engineer to join our semiconductor-focused Forward Deployed Engineering team. This is an IC role that will begin with a strong emphasis on design verification expertise, evaluation curation, and technical leverage across deployments, with the expectation that the person will grow into a broader Forward Deployed Engineering role over time.In the near term, you will serve as a senior technical SME for verification workflows: helping FDEs, Product, and Research teams understand how DV work is done in practice, pressure-testing AI-assisted verification ideas against real engineering workflows, and raising the quality of our solutions through deep domain judgment. You will help the broader team build fluency in verification methodology, tooling, and trade-offs.Over time, we expect this role to expand beyond SME support into broader FDE ownership: partnering directly with customers, shaping deployment strategy, building and iterating production-grade AI systems, driving technical workstreams, and helping turn high-touch semiconductor deployments into repeatable solutions.This is a strong fit for someone who brings deep design verification expertise today and is excited to grow into a customer-facing, systems-building, delivery-oriented FDE role.In this role, you will:Serve as the design verification SME for semiconductor deployments, helping teams reason about verification workflows across block, subsystem, and SoC environmentsShape AI-assisted workflows for test generation, regression triage, debug, root-cause analysis, and coverage closureCurate evaluations with FDEs and customer SMEs, including golden tasks, labeled examples, rubrics, acceptance criteria, and realistic benchmarks grounded in solved issues and real engineering workflowsBuild lightweight prototypes, eval harnesses, and tooling that validate opportunities and improve solution qualityEducate and mentor the broader FDE team on verification concepts, tooling, and methodology so the org can engage semiconductor workflows with greater depth and confidencePartner with FDEs during customer discovery and scoping to translate ambiguous pain points into clear solution hypotheses, success criteria, and technical plansSupport customer-facing technical conversations as a trusted advisor, engaging credibly with technical leadersProgressively take on broader FDE responsibilities, including customer discovery, solution architecture, prototype development, production deployment, and ownership of technical workstreamsMinimum Qualifications:BS/MS in EE, CE, CS, or equivalent with 5+ years of experience in design verification for complex IP, subsystem, or SoC programsDemonstrated success verifying complex hardware systems in industry-standard flows, with deep familiarity in block-, subsystem-, and/or top-level verification methodologiesStrong hands-on expertise in SystemVerilog, UVM, and common simulation/debug tools such as VCS, Questa, Verdi, or equivalentStrong understanding of constrained-random verification, directed testing, scoreboards, checkers, monitors, stimulus generation, regression infrastructure, and coverage analysisStrong knowledge of computer architecture, RTL/microarchitecture, memory systems, coherency, interconnects, and verification methodologyExperience defining verification plans, triaging bugs, and driving debug and root-cause analysis in close partnership with design teamsStrong scripting and automation skills in Python or similar; experience building verification tooling, harnesses, or workflow automation is a plusComfortable operating as a consultative expert who can shape technical direction, evaluate solution quality, and raise the bar across multiple deploymentsExcited to grow beyond domain SME responsibilities into a broader Forward Deployed Engineering role, including hands-on solution building, customer-facing delivery, and ownership of deployment outcomesPreferred Qualifications:Experience across multiple semiconductor companies, design environments, or tool stacks, with a point of view shaped by different verification cultures and methodologiesFamiliarity with adjacent domains such as RTL design, formal verification, emulation, performance analysis, or physical designExperience applying AI/LLM systems to semiconductor workflowsExperience creating reusable evals, methodology assets, or technical playbooksPrior experience in customer-facing, consultative, field engineering, solutions engineering, or technical delivery rolesAbout 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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Gridmatic is a high-growth startup and a new kind of energy company, delivering affordable, clean power by optimizing renewable energy and grid-scale batteries. With offices in the Bay Area and Houston, we bring together Silicon Valley–style innovation with deep, hands-on expertise in real-world power markets and energy retail.As solar and wind become the fastest-growing sources of electricity, variability from weather and grid conditions makes energy prices more volatile. Gridmatic tackles this challenge with industry-leading forecasting and optimization—and gives our team the opportunity to work on problems that truly matter. Forecasting and trading energy are the foundation of what we do. We ingest large-scale data—weather, prices, load, and grid conditions—to build probabilistic machine learning forecasts that drive real operational decisions. Our work directly determines when power is bought, stored, or deployed, turning uncertainty into value for customers and the grid.Our impact is measurable. Gridmatic is the most profitable participant in ERCOT’s wholesale market and operates the top-performing battery asset in CAISO. Profitable without venture capital, we offer a collaborative, low-ego environment where rigorous thinking, autonomy, and continuous learning are core to how we work. The Role We're looking for a Software Engineer to join the team building the core of Gridmatic's battery optimization platform. Our challenges are shaped by the nature of energy markets: optimization models run on tight schedules, bids must be submitted reliably within tight market clearing windows, and data pipelines need to ingest and process market signals continuously. You'll partner with our ML, optimization, and data science teams to bring research into production, and work alongside the Platform Infrastructure team on the compute and orchestration layers that underpin it all. We recognize some candidates may hesitate to apply if they do not have all the listed skills. We encourage interested individuals to apply if they have relevant skills even if they do not have experience in every listed area. What You'll Do: - Build and maintain data pipelines that ingest real-time market and telemetry data and pass these to our forecasting and optimization models - Own production systems using workflow orchestration for battery dispatch and market bidding, where reliability has direct revenue consequences - Partner with ML and optimization researchers to evaluate and productionize bidding strategies e.g. by adding or improving workflow orchestration - Collaborate with the our data and optimization  teams to build reliable data calculations and visualization for  settlement calculations, trading operations, and bid strategy evaluation - Contribute to tooling, observability, and patterns that help the team ship and operate software reliably - Make architectural decisions as we scale the platform alongside our asset portfolio - Join on call rotation to maintain systems you buildWhat We're Looking For: - 4+ years of experience building and operating production software systems - Strong proficiency in Python, including production-grade code beyond notebooks and scripts - Experience with Go, or a background in a similar typed language (Java, Rust, C++) - Solid experience building and operating data pipelines—streaming or batch, at meaningful scale - Hands-on experience with workflow orchestration tools such as Airflow, Flyte, or Temporal - Enthusiasm to learn about and work on details of the application, in this case electricity markets and grid-scale batteries - Systems thinking—understanding how components interact, where failures cascade, and how to build for reliability and efficiency - Clear communication, whether writing a design doc, reviewing code, or explaining a system to someone unfamiliar with it - Comfort in a fast-moving, small-team environment where ownership is broadNice to Have: - Infrastructure-as-code experience with Terraform or similar tools - Hands-on experience with Kubernetes in production (we run on GKE) - Background working with ML, optimization, or research teams to bring models into production - Familiarity with optimization, forecasting, or simulation workflows - Prior work in domains where latency and reliability have direct business consequences - Experience in energy markets, SCADA, or battery management systems 175,000 - 235,000 a yearJoin our team and make a difference! Click below or email us at careers@gridmatic.com.

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About KodiflyKodifly is an AI-first spatial intelligence company transforming infrastructure monitoring and management. Headquartered in Hong Kong Science Park, with an expanded presence in Pakistan and ongoing expansion into the Kingdom of Saudi Arabia, we are backed by HKAI Lab and the NVIDIA Inception program.Our expertise spans 3D point cloud processing, digital twin creation, and LiDAR technology. By integrating AI-powered analytics, digital twins, and real-time spatial intelligence, we help cities and enterprises improve efficiency, quality assurance, and safety across the infrastructure lifecycle. Job DescriptionWe are looking for a Senior Software Engineer to strengthen our core technology stack and lead a high-performing, dynamic team. This role involves hands-on ownership of production-grade, real-world AI and computer-vision systems, with direct impact on product innovation, scalability, and long-term reliability across our platform.Key Responsibilities:Design, develop, and refine algorithms with a strong focus on computer vision and spatial data processing, including GIS-based data presentation.Design, develop, test, and maintain scalable software applications according to specifications.Collaborate with product managers, designers, and stakeholders to translate requirements into robust technical solutions.Write clean, efficient, and well-documented code following best software engineering practices.Conduct code reviews to ensure code quality, maintainability, and performance standards.Debug and resolve complex software defects in a timely manner.Participate in architecture and design discussions, contributing to technical decision-making aligned with business goals.Collaborate with cross-functional teams to integrate software components and resolve integration challenges.Stay up-to-date with emerging technologies and industry trends to continuously improve development practices.Collaborate with QA and assurance engineers to define and execute comprehensive test strategies.Contribute to the continuous improvement of development processes, tools, and workflows.Develop and maintain applications for edge and cloud environments.Participate in the design and development of advanced features leveraging computer vision techniques for digital twin technology.Analyze performance metrics and iterate on solutions to enhance accuracy, robustness, and scalability of spatial data systems.Qualifications:Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, or a related field.4+ years of professional experience in software engineering, preferably with exposure to computer vision systems.2+years experience in Leadership roleProficiency in building applications for cloud and edge environments.Solid understanding of cloud platforms such as AWS, Azure, or GCP and their associated services.Familiarity with edge computing concepts (CDN, caching, edge deployment).Prior exposure to DevOps practices and deployment pipelines.Experience with ROS software and methodologies is a plus.Strong proficiency in C++, Python, or similar programming languages.Solid understanding of software development principles, design patterns, and methodologies.Experience with backend frameworks (e.g., Django) and related libraries.Familiarity with version control systems (Git) and collaboration tools (Jira, Confluence).Knowledge of relational and non-relational databases and data modeling principles.Strong grasp of data structures, algorithms, and object-oriented programming concepts.Experience with unit and integration testing frameworks.Strong analytical and problem-solving skills.Clear communication skills and ability to work effectively in cross-functional teams.Ability to work independently while owning features end-to-end.We Offer:Opportunity to work with state-of-the-art AI and spatial intelligence technology.A collaborative environment where innovation and ownership are encouraged.Competitive salary and share options.Professional growth opportunities and the ability to make a real-world impact in infrastructure safety and efficiency.Fast-track growth opportunities for high performersHigh autonomy and flexibility for leaders to build and own their domainJoin Us at Kodifly:If you’re ready to apply your senior-level computer vision and software engineering skills to solve real-world challenges and build impactful infrastructure technology, Kodifly is looking for you. Apply now and be part of shaping the future of spatial intelligence. 🚀

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About CuspAI CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering. We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock. We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters. We’re on the cusp of the on-demand materials era. Join us.The RoleWe are seeking an ML Research Engineer (Machine Learning Force Fields) to advance our molecular simulation capabilities by developing next-generation computational methods and the robust infrastructure that powers them.Note: You would be joining as a ‘Member of Technical Staff’, but the indicative job title above helps to explain the nature of this role. We are aiming to start interviewing for this role in May and would like to make an offer by the end of June.Your ImpactIn this role, you'll shape the simulation infrastructure that enables CuspAI to evaluate novel material candidates through atomistic physics. You'll bring these simulations to the accuracy and performance needed to power large-scale search campaigns, and design them to be flexible and versatile so they can be adopted quickly to new challenges. Your work will expand what is computationally tractable, accelerating the discovery of the breakthrough materials needed for a sustainable future.What You Will DoModelsTrain, fine-tune, and distill machine learning force fields.Research and develop novel ML force field architectures suited to production simulation workloads.Systems & infrastructureIntegrate these models into public and in-house high-performance simulators.Develop training and inference architectures for large-scale training, data generation, and simulation.Distribute these workloads via Ray to scale across our compute infrastructure.Build the system with modularity in mind, so components can be reused across many kinds of chemistry.Science & collaborationBuild an active learning system that closes the loop between simulation, data generation, and training.Develop interfaces that make the system easy for domain scientists to use and extend.Collaborate closely with computational chemists on density functional theory (DFT) data generation and validation.Must Have Skills and Qualifications:You are motivated by the opportunity to build foundational tools and infrastructure that enable scientists to work on world-changing challenges.Demonstrated technical excellence in both research and implementation; you have a track record of building high-quality, performant systems rather than just writing theoretical papers.Exceptional coding skills with a strong command of modern software engineering practices.Deep production or research experience with distributed machine learning systems.PhD (or comparable professional experience) in a relevant quantitative field (e.g. Computer Science, Physics, Applied Mathematics, Computational Science, Machine Learning) with a strong foundation in computational methods.A genuine and explicit interest in the potential applications of AI within materials science and chemistry.Bonus Points (But Not Critical):Experience with deploying, training, and modifying machine learning force fields. Note: this is a strong bonus, but not required for exceptional candidates.Experience with management of atomistic data.Experience with Density Functional Theory.Experience with molecular simulation methods (MCMC, MD).Experience with graph neural network design.Experience with Cloud infrastructure and Kubernetes.A track record of published research at top-tier venues in ML (e.g. NeurIPS, ICML) or computational physics.Additional ConsiderationsThis role could be based in our Cambridge, London, Amsterdam or Berlin offices, with the expectation of being in the office three days per week. Additionally, there may be regular travel required to other locations for collaboration and project work.What We OfferA competitive salary plus equity package so you have a stake in the success of the company28 days holidayProfessional development budget for scientific conferences and technical trainingOpportunity to work at the forefront of AI-driven scientific discovery with world-class researchersDirect impact on advancing materials science through cutting-edge technologyCollaborative environment bridging AI research, computational chemistry, and experimental science Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world. CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law. We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team. Please let us know If you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.

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About CuspAI CuspAI is the frontier AI company on a mission to solve the breakthrough materials needed to power human progress. While nature took billions of years to perfect molecules, we are harnessing AI to unlock trillion-dollar materials breakthroughs in months, not millennia. Our founding team is the most cited in the world, comprised of world-class researchers in AI, chemistry and engineering. We are working on some of the hardest and most important challenges including energy, clean water, the future of compute, and carbon capture, and this is just the start of what our 'search engine' for next-generation materials will unlock. We invite you to be part of a diverse, innovative team at the intersection of AI and materials science, working to create impactful partnerships that drive innovation, scalability, and industry collaboration. This work matters. Your work matters. We’re on the cusp of the on-demand materials era. Join us.The RoleDue to expansion into a new area, we are seeking a Scientific Software Engineer (Polymer Simulations) to bridge the gap between our frontier AI models and real-world industrial materials challenges.Note: You would be joining as a ‘Member of Technical Staff’, but the indicative job title above helps to explain the nature of this role.Your ImpactYou will build our atomistic polymer simulation capability from the ground up by designing the workflows, establishing the methodology, and setting the standard for how simulation integrates with our AI platform and experimental partners. This is foundational work that will directly underpin how CuspAI bridges the atomic scale and the macroscopic properties that determine whether a material succeeds or fails in the real world.What You Will DoMethod Development & ResearchDesign and implement atomistic simulation workflows for polymer systems from polymerisation and melt equilibration through to production runs.Reach beyond MD and implement complementary simulation techniques to tackle complex industry problemsCollaborate with our AI Research team to integrate machine learning models into atomistic simulation workflows, helping bridge the gap between learned representations, simulations, and experiments. .Experimental Validation & Partner CollaborationWork closely with experimental partners to ensure simulation outputs are grounded in and validated against real lab measurements — trends must be reproducible, and results must be explainable.Translate partner materials challenges into concrete simulation strategies, then execute and deliver findings with the clarity and rigour that industrial collaborations require.Interdisciplinary CollaborationAct as internal expert on polymer science, providing guidance to AI researchers on physical constraints and realistic material behaviours.Work fluidly across a team of ML researchers, computational chemists, and experimentalists — contributing independently while building on a wide base of complementary expertise around you.Contribute to CuspAI's core infrastructure and roadmap for multi-scale materials discoveryMust Have Skills and Qualifications:Extensive expertise in polymer simulation. You've worked across multiple projects and know from experience what breaks and why. You don't just run simulations; you understand them.Hands-on experience with mapping simulations onto experiments including proven ability to reproduce and explain real-life trends.The ability to build simulation workflows from scratch. We need someone who can design and implement methods, not just configure existing pipelines. When the right tool doesn't exist, you write it.Readiness to reach beyond your primary toolkit. Polymer simulations are intrinsically multi-method, multi-scale, and multi-discipline, and we expect you to be able to pick up and implement approaches as the science demands.Strong software engineering skills, with proficiency in Python, large-scale projects, and hands-on experience with simulation packages such as GROMACS or LAMMPS, and ASE or commercial equivalents.The communication skills to work effectively across disciplines — AI researchers, computational chemists, and experimentalists will all be your collaborators. Bonus Points (But Not Critical):A PhD or equivalent in Materials Science, Physics, Chemistry, or Chemical Engineering, with a focus on multi-scale or polymer modelling.Prior experience in AI4Science such as generative molecular models, machine learning force fields, or property predictions.Familiarity with first-principles simulation methodsExperience with HPC environments or cloud-based simulation at scale.Prior experience in a startup or client-facing technical role.Additional ConsiderationsThis role could be based in our Cambridge, London, Amsterdam or Berlin offices, with the expectation of being in the office three days per week. Additionally, there may be regular travel required to other locations for collaboration and project work. What We OfferA competitive salary plus equity package so you have a stake in the success of the company28 days holidayProfessional development budget for scientific conferences and technical trainingOpportunity to work at the forefront of AI-driven scientific discovery with world-class researchersDirect impact on advancing materials science through cutting-edge technologyCollaborative environment bridging AI research, computational chemistry, and experimental science Join us in shaping the future of materials with AI. Together, we can create groundbreaking solutions for a more sustainable world. CuspAI is an equal opportunities employer committed to building a diverse and inclusive workplace. We do not discriminate on the basis of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy or related condition (including breastfeeding), veteran status, or any other basis protected by applicable law. We actively encourage applications from all backgrounds and value the unique perspectives and contributions that diversity brings to our team. Please let us know If you require any specific adjustments during or after the interview process. We will do everything we can within reason to accommodate.

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Who We AreServal is an AI-native automation platform transforming how enterprises operate. We build intelligent agents that understand real-world workflows and execute them end-to-end — replacing manual processes and rigid legacy systems with adaptive, learning software. Founded in early 2024, Serval is already trusted by companies like Fox, Notion, Perplexity, Vercel, Mercor, LangChain, and Verkada to automate high-volume, high-friction operational work across their organizations. At the core of Serval is an agentic AI platform that turns natural language into production-grade workflows. Our agents don’t just respond to requests — they reason, take action across systems, and continuously improve with usage. What began with operational use cases has quickly evolved into a horizontal AI automation layer used across IT, HR, Finance, Security, Legal, and Engineering. Our mission is to eliminate repetitive, manual work across the enterprise and give teams leverage through intelligent automation. Long term, we’re building the universal AI operations layer — a system of agents that sits across business functions and runs the workflows that keep modern companies moving. We’re backed by leading investors including Sequoia Capital, Redpoint Ventures, Meritech, First Round, General Catalyst, Elad Gil, and others, and founded by product and engineering leaders from Verkada.Role OverviewAI is rewriting how companies discover and choose what to buy, and we need you to build the agent-powered marketing engine that makes Serval impossible to ignore. You'll design the agents that run growth marketing end-to-end, from content and campaigns to AI search visibility and the systems that connect them. You'll partner closely with the Head of Growth, content, design, and product marketing to turn marketing workflows into reliable, self-improving programs.Who You AreA builder at heart, able to scope what matters, prototype it, and ship it yourself.Living on the AI frontier – you've built agents that work and you bring fresh ideas and techniques to the team as fast as the field moves.A systems thinker who builds for the long run, designing things that run and improve on their own by measuring results, catching issues, and iterating.Comfortable in ambiguity, owning your work end-to-end, and moving without waiting to be told what to build next.What You'll DoOwn Serval's AEO strategy, including the structured data, schema, and content systems that drive visibility in LLM responses.Build AI agents that autonomously run marketing workflows including content drafting, brief writing, campaign launches, and creative testing.Design evals, guardrails, and feedback loops so agents stay reliable in production and improve over time.Use performance data to prioritize what to automate next, partnering closely with content, design, and product marketing to bring shared initiatives to life.Architect publishing and distribution systems across CMS, data sources, and channels so content moves end-to-end with minimal manual work.Run experiments across workflows, content structures, and distribution strategies, treating each deployment as a hypothesis.Codify what works into reusable templates, internal tooling, and documentation.What You'll Need4+ years of experience in marketing engineering, growth engineering, product management, or a similar role.A foundation in programming and systems thinking to confidently wire together agents, APIs, and data flows.Hands-on experience building agents or LLM-powered systems.Strong analytical skills, with the ability to turn quantitative data and qualitative signals into clear, actionable decisions.A high level of ownership and initiative, with the ability to scope, prototype, and ship without waiting for direction.Familiarity with how search engines and AI models discover, index, and surface content, with experience in structured data such as schema.org or JSON-LD a plus.Experience in B2B SaaS or high-growth startups is a plus.What We OfferImpact: Be a key player in shaping the success of our product and company.Growth: Build a fundamentally new AI product offering with the support of our experienced team and investors. Grow rapidly with the company.Culture: Join a culture that values innovation, ownership, accountability, and fun.

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About Us Legora is on a mission: to redefine how legal work gets done. From the very start we have been very clear about the fact that we are not building a solution for lawyers, we are building it with them, because it is the only way to make sure it gets done the right way; working side-by-side every step of the way.Our AI-native workspace empowers legal professionals not just to work faster - but to ask better questions, unlock new insights. Every day, we push the boundaries of legal tech to make complex processes smarter, faster, and more human. From thousands of documents analysed in minutes to intelligent workflows designed in collaboration with leading practices, we’re turning possibility into reality.Today we are trusted by global firms like Cleary Gottlieb, Goodwin, Bird & Bird and Linklaters in over 40 countries, but we have no plans on stopping here. We ship fast, we iterate effectively, and we scale rapidly - not by accident, but by design.When you join Legora, you become part of a team that believes "good enough" isn’t good enough and that the way to win is together, by empowering lawyers to do their best work with technology that truly understands them. If you’re excited by building from first principles, working with exceptional people, and accelerating change in a high-stakes, high-impact domain—then this is the moment and the place.We’re not just shaping the future of legal tech — we’re defining it. Ready to join us in building the intelligent future of law? The roleAre you ready to take your AI career to the next level? At Legora, we’re on a mission to revolutionize the legal industry with cutting-edge AI and LLM tech. We’re seeking software engineers to join our fast-moving team, where you’ll work on technically difficult projects with the support of an amazing team, and help redefine how legal professionals work.*This is a Stockholm-based, 5-day in-office role, we believe building together in person drives better outcomes.What you will be doing:Architect and implement all AI and LLM features end-to-end for our web platformEnsure we utilize the latest and greatest LLM features, agentic tools etcWork with technologies such as React, Node.js, AWS, Azure and KubernetesTake ownership of our codebase, balancing high-quality code, security and speed of developmentOwn and drive forward PoCs and solve broad technical challenges Who you areA passionate software engineer with a few years of experience implementing and evaluating AI and LLM applicationsA strong coderProficient in languages like Node.JS, with an emphasis on clean, efficient, and maintainable codeYou’re autonomous and take pride in the systems you architectYou’re a low ego, true team playerYou’re a problem solver who’s not afraid to come up with creative solutions and think holistically about applied AILegora is an Equal Opportunity EmployerAt Legora, we believe great teams are built on diversity of thought and experience. We’re proud to be an equal opportunity employer and committed to creating an inclusive, high-performance culture where everyone can do their best work. We welcome people of all backgrounds and don’t discriminate based on race, color, religion, national origin, gender, gender identity or expression, sexual orientation, age, disability, veteran status, or any other characteristic protected by law.

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About UsAt LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.Today, LangChain, LangGraph, LangSmith, and Fleet are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.About the TeamThe Deployed Engineering team works directly with companies building and running AI agents in production, helping turn ideas and prototypes into systems teams can rely on.This is a hands-on, highly technical team that partners closely with customer engineers across the full lifecycle, from pre-sales evaluations to post-deployment advisory work. The focus is on achieving the technical win, co-designing agent architectures, and helping customers operate agents reliably at scale using the LangChain suite.Deployed Engineers sit at the intersection of engineering, product, and go-to-market, shaping how LangChain is adopted in the field and feeding real-world insights back into the platform.About the RoleThe Deployed Engineer…You’ll work on some of the hardest problems in applied AI — not demos, not research, but systems that real teams depend on in production. The feedback loop is fast, the impact is visible, and the work you do directly shapes how AI agents are built in the real world.What You’ll DoCo-architect and co-build production AI agents with customer engineering teamsOwn the technical win in pre-sales by designing POCs, answering deep technical questions, and guiding evaluationsHelp customers deploy and operate agent-based applications such as conversational agents, research agents, and multi-step workflowsAdvise customers post-sale on architecture, best practices, and roadmap-level decisionsRun technical demos, trainings, and workshops for developer audiencesSurface field feedback and contribute reusable patterns, cookbooks, and example code that scale across customersOccasionally contribute code upstream when it meaningfully improves customer outcomesWhat You’ll Bring3+ years in a relevant technical role (software engineering, customer engineering, solutions engineering, founding/product engineering), ideally in a startup or scale-upStrong Python, JavaScript and systems fundamentalsHave designed agent-based or LLM-powered applications beyond simple API calls, including multi-step workflows, orchestration, and failure handlingAre comfortable working directly with customers during POCs, architecture reviews, and technical evaluationsCan explain technical tradeoffs clearly and build trust with developer audiencesTake responsibility for outcomes, not just recommendationsHave a bias toward action and enjoy figuring things out as you goAre excited about operating AI agents in production, not just building demosNative French SpeakerNice to Have’sYou’ve deployed AI agents in production, especially using LangChain, LangGraph, or similar frameworksWorked with LLM evaluation, observability, or guardrailsHave experience with cloud environments (AWS, GCP, Azure), containers, and basic Kubernetes conceptsHave shipped and operated production software and are comfortable owning systems under real-world constraintsCompensation Philosophy:We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.BenefitsBenefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

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About the CompanyAt Harmonic, we are building a mathematical reasoning engine that operates with absolute precision. While most AI makes maximum-likelihood guesses, Harmonic's Aristotle uses Lean 4 and reinforcement learning to verify its reasoning and results.Following our Gold Medal-level performance on the 2025 International Math Olympiad (IMO) and the successful resolution of long-standing open problems, we are proving that AI can master the most rigorous domains of human thought. Backed by some of the world’s most prominent investors, we are intentionally scaling an elite technical team.About the RoleWe are looking for a pragmatic, Software Engineer to own the productionization of our research pipelines. This is an implementation-heavy role designed for an engineer who can take a nascent research idea and build the robust, scalable machinery required to prove it at scale within our cloud infrastructure.Key ResponsibilitiesPipeline Engineering: Build and manage end-to-end ML pipelines (ETL and automated evaluation) that are the bedrock of our RL research.Bottleneck Resolution: Identify and refactor inefficient research code. You act as the primary engineer ensuring that a promising idea reaches its full potential through scalable code.Standardization: Establish best practices for versioning, experiment tracking, and CI/CD for ML models to ensure reliability.Cloud Infrastructure & Observability: Manage the deployment and scaling of workloads on Kubernetes. Implement the tooling and telemetry that allows the team to understand agent behavior and training health at a glance.Minimum QualificationsBS in Computer Science, a related technical field, or equivalent industry experience2+ years of relevant industry experienceExpert-level Python skills and a disciplined approach to software engineering (testing, versioning, and modular design).Experience building and managing end-to-end ML pipelines in a production or research-intensive environment.Preferred QualificationsFull-stack ML experience: Comfortable moving from data engineering to model debugging.Experience refactoring research-grade code into high-quality, scalable production packages.Proven ability to design and implement complex data-loading and evaluation systems for non-deterministic models.Experience with workflow orchestration tools (e.g., Kubeflow, Airflow, or Metaflow).Experience managing large-scale experiments on cloud providers (AWS, GCP, or Azure).Proven track record collaborating directly with researchers to translate algorithmic requirements into engineering roadmaps.Hands-on experience with containerization (Docker) and orchestration (Kubernetes).What We OfferUnlimited PTO401(k) matching100% employer-paid health, vision, and dental benefits for employees and 50% coverage for dependents. Harmonic offers varied health coverage options to select what is best for you and your family.Health Savings Account (HSA) available for qualifying health plans Visit our company blog to learn more about what we are working on! Equal Opportunity StatementHarmonic is committed to diversity and inclusivity in the workplace. We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.

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About the CompanyAt Harmonic, we are building a mathematical reasoning engine that operates with absolute precision. While most AI makes maximum-likelihood guesses, Harmonic's Aristotle uses Lean 4 and reinforcement learning to verify its reasoning and results.Following our Gold Medal-level performance on the 2025 International Math Olympiad (IMO) and the successful resolution of long-standing open problems, we are proving that AI can master the most rigorous domains of human thought. Backed by some of the world’s most prominent investors, we are intentionally scaling an elite technical team.About the RoleWe are developing reinforcement learning systems at a scale where standard abstractions frequently fail. Unlike labs that operate primarily through high-level wrappers, we own the entirety of our RL stack. This ownership spans from low-level environment simulators and custom communication primitives to our distributed training loops and inference engines.We are seeking engineers who view existing libraries as a baseline and the hardware speed itself as the true target. You will be responsible for the architecture powering our agents, with a relentless focus on maximizing the throughput of our reinforcement learning and production workflows.Key ResponsibilitiesTotal Stack Ownership: Maintain and optimize our proprietary RL training and serving infrastructure. You have the authority to refactor any layer—from the Python API down to the CUDA kernels—to achieve peak performance for foundation model workloads.Optimized Training: maximize the throughput of our reinforcement learning system from data generation to model training with sharded multi-node training and inference algorithms.High-Performance Serving: optimize our inference stack for high-throughput reinforcement learning and low-latency LLM production traffic. Tune the inference engine, router, and scheduler, down to custom kernels if need be.Compute Optimization: Identify and resolve performance bottlenecks within our distributed clusters, ensuring optimal throughput and memory efficiency for multi-billion parameter models, balancing memory constraints with compute-heavy training cycles.Minimum QualificationsBS in Computer Science or a related technical field, or equivalent industry experience2+ years of relevant, hands-on industry experienceProficiency in PythonExperience building or maintaining components within ML frameworks (e.g., PyTorch, JAX, or TensorFlow).Proficiency in either:Understanding of distributed training concepts and collective communication primitives (e.g., NCCL).ORPractical experience deploying and profiling models on GPU-accelerated cloud infrastructure.Preferred QualificationsMS or PhD in Computer Science, Mathematics, or a related field.5+ years of relevant, hands-on industry experienceProficiency in C++Experience writing or improving kernels (Triton, CuTeDSL, TileLang, CUDA, CUTLASS, ThunderKittens) to resolve low-level bottlenecks.Proven success deploying performant inference at scale using open-source or custom inference engines, routers, etc.Direct experience scaling models via FSDP, Tensor Parallelism, or related sharding techniques on multi-node GPU clusters.Experience designing reinforcement learning systems for high-throughput training and asynchronous data sampling.What We OfferUnlimited PTO401(k) matching100% employer-paid health, vision, and dental benefits for employees and 50% coverage for dependents. Harmonic offers varied health coverage options to select what is best for you and your family.Health Savings Account (HSA) available for qualifying health plansVisit our company blog to learn more about what we are working on!Equal Opportunity StatementHarmonic is committed to diversity and inclusivity in the workplace. We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status.

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About Us:webAI is pioneering the future of artificial intelligence by establishing the first distributed AI infrastructure dedicated to personalized AI. We recognize the evolving demands of a data-driven society for scalability and flexibility, and we firmly believe that the future of AI lies in distributed processing at the edge, bringing computation closer to the source of data generation. Our mission is to build a future where a company's valuable data and intellectual property remain entirely private, enabling the deployment of large-scale AI models directly on standard consumer hardware without compromising the information embedded within those models. We are developing an end-to-end platform that is secure, scalable, and fully under the control of our users, empowering enterprises with AI that understands their unique business. We are a team driven by truth, ownership, tenacity, and humility, and we seek individuals who resonate with these core values and are passionate about shaping the next generation of AI.About the Role:We are looking for a Data Platform Engineer to design and build the connective tissue between real-world data systems and our AI platform. You will create scalable, reusable data connectors and transformation layers that make heterogeneous data sources usable for downstream inference. This role sits at the intersection of distributed systems, data infrastructure and applied AI. This role will act in terms of platform primitives, not pipelines.Key Responsibilities:Design and build robust connectors across SQL / NoSQL databases, APIs (REST / GraphQL), SaaS platforms (e.g., CRM, storage systems)Interpret and model heterogeneous source schemasTransform raw source data into formats optimized for AI inferenceWork closely with ML, applied AI and forward deployed teams to define feature expectationsCollaborate with infrastructure teams to design and ship hosted data pipelinesOptimize for latency, consistency, and edge constraintsDesign resilient ingestion patterns for unreliable or rate-limited systemsBuild logging, monitoring and debuggability into all integrationsQualifications:Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experienceProven experience building connectors against enterprise systems (SQL/NoSQL databases, Salesforce, S3, REST/GraphQL APIs)Systems instinct to architect a platform primitive, not a one-off integrationFamiliarity with inference pipelines or ML-adjacent data preparation preferredComfortable working in a startup environment with ambiguity and evolving requirementsBenefits:Competitive salaryEquity options401k matchComprehensive health, dental, and vision benefits package.$200/mos Health and Wellness StipendContinuing Education supportFree parking, for in-office employeesFlexible time offParental, Bereavement LeaveSupplemental Life Insurance webAI is an Equal Opportunity Employer and does not discriminate against any employee or applicant on the basis of age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We adhere to these principles in all aspects of employment, including recruitment, hiring, training, compensation, promotion, benefits, social and recreational programs, and discipline. In addition, it is the policy of webAI to provide reasonable accommodation to qualified employees who have protected disabilities to the extent required by applicable laws, regulations and ordinances where a particular employee works.

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LandingAI is building the infrastructure to make the world’s documents computable. We are an AI-native company transforming unstructured and dark data into trusted, structured, auditable data that software can understand and act on. Our focus is on the hardest document understanding problems: multiple document types, complex layouts, tables, images, handwriting, and mixed modalities within and across workflows. Founded by Andrew Ng, LandingAI has brought together some of the strongest AI Engineers and Machine Learning Engineers in the industry, with deep expertise in visual AI, agentic systems, foundation models, and production ML infrastructure. We build from the ground up where it matters, move fast with the latest AI coding tools and agentic developer workflows, and invest in the compute and technical environment needed to do exceptional work. Our work is grounded in three core strengths: Agentic systems built for production. We have been early builders of agentic AI systems and have applied that work in the real world through Agentic Document Extraction (ADE), our platform for parsing, understanding, and extracting information from complex documents with traceability, control, and production-grade reliability. A data-centric mindset. We bring a rigorous, practical approach to model quality, edge cases, evaluation, and real customer data, because solving document understanding in production requires far more than strong benchmark performance. A vision-first approach to foundation models. We build from the ground up where it matters, including specialized document models and agentic systems, because solving real document understanding problems requires more than stitching together generic components. Since launching Agentic Document Extraction in early 2025, LandingAI has grown quickly by bringing a modern, AI-native approach to a legacy intelligent document processing market ready for disruption. This is a place for builders. If you want to work on real technical depth, move quickly, take ownership, and help define the future of document intelligence, LandingAI is the place to do it.Key Responsibilities Be a driving force for the team's agentic coding practice - establishing patterns for spec-driven development, context engineering, and multi-agent orchestration that compound team output. Design, develop, and maintain AI-powered applications and services, focusing on high availability, performance, and reliability. Work closely with Machine Learning Engineers, building AI capabilities from early R&D prototyping to scalable operation in multiple production stacks. Build ML services designed for low-latency or high-throughput, and optimized for high cost efficiency. Lead cross-functional initiatives, collaborating with Machine Learning Engineers, Product Managers, and other teams to align technical solutions with business needs. Drive innovation by making strategic technical decisions, setting best practices, and mentoring engineers to elevate the team’s technical bar. Improve ML development process by enhancing the internal ML platform, facilitating data sourcing, and enabling ML observability for deployed services. Required Skills Fluency with agentic coding tools (Claude Code, Codex or equivalent). Experience writing effective specs, managing repo context, and reviewing/verifying agent output. 5+ years of experience in software development, with a strong backend and ML engineering background. Experience working with cloud native technologies (Docker, Kubernetes). Experience working with cloud platforms (AWS, GCP, or Azure). Experience with building ML systems, from early prototype, to operating at scale in production. Strong software architecture skills, with experience designing and scaling distributed systems and cloud-based applications. Experience mentoring engineers and contributing to team-wide technical direction. Strong communication skills, with the ability to translate technical challenges into business impact. Nice to Have Experience with ML frameworks like pytorch. Experience with serving ML models and LLMs using frameworks like vllm. Experience with developer-facing products and building intuitive APIs. 190 - 220 a yearThis role is onsite at our Mountain View HQ, with the expectation to work from the office on a daily basis. As we are a global team, the position also requires flexibility to collaborate across international time zones.

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LandingAI is building the infrastructure to make the world’s documents computable. We are an AI-native company transforming unstructured and dark data into trusted, structured, auditable data that software can understand and act on. Our focus is on the hardest document understanding problems: multiple document types, complex layouts, tables, images, handwriting, and mixed modalities within and across workflows. Founded by Andrew Ng, LandingAI has brought together some of the strongest AI Engineers and Machine Learning Engineers in the industry, with deep expertise in visual AI, agentic systems, foundation models, and production ML infrastructure. We build from the ground up where it matters, move fast with the latest AI coding tools and agentic developer workflows, and invest in the compute and technical environment needed to do exceptional work. Our work is grounded in three core strengths: Agentic systems built for production. We have been early builders of agentic AI systems and have applied that work in the real world through Agentic Document Extraction (ADE), our platform for parsing, understanding, and extracting information from complex documents with traceability, control, and production-grade reliability. A data-centric mindset. We bring a rigorous, practical approach to model quality, edge cases, evaluation, and real customer data, because solving document understanding in production requires far more than strong benchmark performance. A vision-first approach to foundation models. We build from the ground up where it matters, including specialized document models and agentic systems, because solving real document understanding problems requires more than stitching together generic components. Since launching Agentic Document Extraction in early 2025, LandingAI has grown quickly by bringing a modern, AI-native approach to a legacy intelligent document processing market ready for disruption. This is a place for builders. If you want to work on real technical depth, move quickly, take ownership, and help define the future of document intelligence, LandingAI is the place to do it. Key Responsibilities Being a driving force for the team's agentic coding practice - establishing patterns for spec-driven development, context engineering, and multi-agent orchestration that compound team output. Owning and defining architecture for AI-powered applications and services, ensuring scalability, security, and maintainability across teams. Designing, developing, and deploying backend infrastructure and AI services with a focus on high availability, performance, and reliability. Leading cross-functional initiatives, collaborating with Machine Learning Engineers, Product Managers, and other teams to align technical solutions with business needs. Driving innovation by making strategic technical decisions, setting best practices, and mentoring engineers to elevate the team’s technical bar. Improving developer experience by building internal tooling, streamlining workflows, and optimizing deployment pipelines. Ensuring seamless data flow, building high-throughput, secure, and scalable data pipelines to support AI model training and deployment. Championing best practices in software engineering, ensuring high-quality code, rigorous testing, and well-documented design decisions. Required Skills 5+ years of experience in software development, with a strong backend / full-stack engineering background. Fluency with agentic coding tools (Claude Code, Codex or equivalent). Experience writing effective specs, managing repo context, and reviewing/verifying agent output. Expertise in backend development, with proficiency in Python and/or Node.js and modern web frameworks like FastAPI, Flask, Express.js, Next.js Strong software architecture skills, with experience designing and scaling distributed systems and cloud-based applications. Hands-on experience with Docker and Kubernetes for containerization and orchestration. Database expertise, including SQL, NoSQL, and data streaming solutions. Experience working with cloud platforms such as AWS, GCP, or Azure. Proficiency in software engineering best practices, including code reviews, unit testing, CI/CD pipelines, and system design. Experience mentoring engineers and contributing to team-wide technical direction. Strong communication skills, with the ability to translate technical challenges into business impact. Proven track record of leading fullstack projects, from early prototypes to production systems. Nice to Have Familiarity with Stripe, subscription management. Exposure to computer vision, LLMs, or multimodal AI applications. Experience with developer-facing products and building intuitive APIs. 190 - 220 a yearThis role is onsite at our Mountain View HQ, with the expectation to work from the office on a daily basis. As we are a global team, the position also requires flexibility to collaborate across international time zones.

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About the Role 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. Please see our privacy policy at https://www.together.ai/privacy