About the Team The Coding team is reimagining how software is built in the AI era. We build tools and workflows that help software engineers work faster, tackle more ambitious projects, and spend less time on repetitive tasks. AI has already transformed how code is written, but software engineering extends far beyond coding. Our mission is to apply AI across the entire software development lifecycle (SDLC) — from design and implementation to code review, testing, debugging, issue remediation, maintenance, documentation, and user support. The team is also responsible for developer-facing Codex experiences including the Codex IDE Extension and the terminal interface, which are used daily by developers ranging from individual open-source contributors to some of the world’s largest engineering organizations. The team also works closely with the open-source software community, building tools that help maintainers and contributors manage increasingly complex projects. We believe AI can make open-source development more sustainable by reducing the operational burden of reviewing contributions, triaging issues, maintaining quality, and supporting growing communities. By building the future of software development, we're helping advance OpenAI's mission of ensuring that the benefits of AI reach people around the world. About the Role We’re hiring a Full Stack Software Engineer to help invent the next generation of AI-powered software development workflows. “Full stack” in this role means much more than traditional frontend and backend development. You'll own complete product experiences, spanning user interfaces, workflow orchestration, agent and prompt design, backend systems, and cloud infrastructure. This is a highly product-oriented role. You'll work directly on the workflows developers use every day, identifying bottlenecks and rethinking how software gets built in a world where AI agents are active participants in the development process. The features you ship will inf
Jobs in United States
Product Data Management Engineer in United States
4,445 active opportunities · Updated October 2026
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Explore current product data management engineer jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.
$226K – $285K/yr
About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role As a Supply Chain Program Manager, you will own material readiness and supply chain execution for critical hardware programs spanning custom silicon, systems, memory, storage, networking, and rack infrastructure. You will work cross-functionally with Engineering, Strategic Sourcing, Manufacturing Operations, Finance, Planning, Quality, and external suppliers to develop and execute scalable supply strategies that support aggressive product development and deployment timelines. This role requires deep understanding of hardware supply chains, material planning, NPI execution, supplier management, and operational scaling in constrained and rapidly evolving environments. In this role you will: Material Readiness & Supply Planning - Own end-to-end material readiness across NPI and production phases, including building the necessary framework and processes for enablement. Drive supply planning and execution for long lead-time and constrained commodities including ASICs, HBM, DDR, SSDs, networking, optics, power, thermal, and mechanicals. Build and manage material readiness plans aligned to proto/pre-EVT, EVT, DVT, PVT, and mass production schedules. Monitor supply health, lead times, inventory positions, allocation risk, and capacity constraints. Drive shortage management, allocation mitigation, and recovery planning. Coordinate supply commits, forecast alignment, and supply continuity planning with suppliers and manufacturing partners. Cross-Functional Program Ma
About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu
This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea
About the Team The Strategic Finance team provides financial insights and guidance to support the organization's long-term goals and strategies. We partner across the business to allocate and deploy our resources for the highest impact outcomes. About the Role We are hiring a Hardware Finance Manager, Consolidations & Systems to own the consolidated financial reporting, forecasting cadence, and financial systems across our hardware organizations (Io and Robotics). This role sits at the intersection of Hardware Finance, central FP&A, Accounting, and Finance Systems, and is responsible for ensuring leadership has a single, accurate, and timely financial view of the hardware business. This role will serve as the embedded owner of the hardware financial backbone, with end-to-end responsibility for consolidated P&L reporting, forecasting and variance analysis, and the systems and processes that enable scalable, decision-ready insights. You will help ensure hardware financials are consistent, auditable, and fit for executive and board-level decision-making as the organization scales in size, complexity, and capital intensity. We have a strong preference for candidates who can be based in our San Francisco HQ. 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 oversee multiple areas of responsibility: Own end-to-end consolidated financial reporting for all hardware organizations (Io and Robotics), delivering a single, integrated P&L view across R&D, Product, Revenue, COGS, and OpEx. Establish and run the hardware financial operating cadence, including monthly close, forecasting, reforecasting, and variance analysis, ensuring consistency and accountability across teams. Serve as a key finance partner to Hardware Finance leads, central FP&A, and Accounting, aligning bottoms-up plans with accounting actuals and enterprise reporting requirements. Build and maintain consoli
About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the role Our Sales team has a unique mission to help customers understand the deep impact that highly capable AI models can bring to their business and users. This role is a mixture of technical understanding, vision, partnership, and value-driven strategy. You’ll be a key driver of opportunities through the entire sales cycle, from pipeline generation to closure. You’ll work with researchers, engineers, and solution strategists to help customers evolve their industry with AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you'll: Manage a portfolio of customer accounts, developing and executing strategies for a comprehensive account plan Support your customer accounts from initial engagement to successful deployment, expansion, and through to renewal Develop new and existing accounts through pipeline generation, discovery, evaluation, and successful adoption Partner with solutions and research engineering to build and execute complex customer programs and projects Own a revenue target Manage revenue forecasts Analyze key account metrics to create reports and provide insights to internal and external stakeholders Closely monitor the industry landscape (people, competitors, partners, etc.) to contribute to product roadmap and
About The Team OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. The Technical Accounting team plays a crucial role in helping OpenAI navigate complex, judgmental, and rapidly evolving accounting matters with rigor and clarity. We aim to bring both technical excellence and strong business partnership to some of the most novel accounting questions in the industry. About The Role OpenAI seeks a Director, Technical Accounting, Revenue & Strategic Partnerships to set the technical revenue accounting strategy for the company's largest, most complex, and highest-risk commercial arrangements. This leader will personally assess novel fact patterns, establish and defend the accounting position, and shape deal structures before execution across enterprise contracts, strategic partnerships, API and consumption-based offerings, credits and incentives, revenue share, multi-party arrangements, and emerging product monetization models. This role will be the senior technical accounting partner to Revenue Accounting, Sales, Product, Legal, Tax, Strategic Finance, Business Development, Deal Desk, Billing, Financial Reporting, Internal Controls, and external auditors. The core mandate is technical judgment: independently synthesize the full contractual and economic substance, identify alternatives and second-order implications, resolve ambiguity under ASC 606 and related U.S. GAAP, and communicate a clear recommendation to executives and auditors. Operational know-how is essential to translate conclusions into billing, close, disclosures, systems, and controls, but process ownership is not the center of the role. In This Role, You Will Partner closely with Revenue Accounting, Sales, Product, Legal, Tax, Strategic Finance, Business Development, Deal Desk, Billing, Financial Reporting, and external auditors. Identify non-standard revenue arrangements early and evaluate them under ASC 606. Advise on thoughtful deal structurin
About the Team The Hardware Health and Observability team owns the end-to-end health lifecycle of OpenAI’s global compute fleet. Our mission is to maximize healthy, usable compute across accelerator vendors, generations, cloud providers, and regions through reliable health signals, automated remediation, and scalable operational tooling. We build the systems that observe, detect, remediate, and verify hardware issues across GPUs, CPUs, networking, and platform infrastructure, enabling frontier model training and inference workloads to run reliably at hyperscale. We are the last line of defense for the success of OAI’s production and research workloads. About the Role On the Hardware Health and Observability team, you’ll build critical infrastructure that keeps OpenAI’s largest compute clusters healthy and operational at scale. Even small numbers of unhealthy systems can impact large-scale training and inference workloads. This team focuses on minimizing downtime, improving fleet efficiency, and ensuring compute resources remain continuously available to researchers and product teams. Engineers on this team own problems end-to-end, from defining health signals and debugging failures to building automated remediation systems that operate across millions of GPUs globally. In this role, you will: Define and maintain health signals across GPUs, CPUs, networking, and platform infrastructure. Build and evolve health checks that detect, remediate, and verify failures at scale. Ensure critical health checks execute with minimal latency to maximize workload uptime. Investigate hardware failures and system-level issues across large-scale compute environments. Own node lifecycle workflows including drain, quarantine, repair, RMA, and return-to-service processes. Build automation and tooling that enables global cluster management with minimal manual intervention. Partner with workload, reliability, and provider teams to integrate health signals into training and inference system
AI Systems Engineer - Codex Core Agents About The Team The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex. About The Role We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements. What You’ll Do Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely. Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments. Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures. Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to
About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role We’re seeking an exceptional Principal-level Offensive Security Engineer focused on deep, hands-on penetration testing of OpenAI’s agent-powered products, infrastructure, and model-integrated application surfaces. You’ll assess complex systems end to end, identify realistic vulnerabilities, validate exploitability and impact, and partner closely with engineering teams to drive durable fixes. This role will be primarily focused on continuously testing our agent-powered products like Codex and Operator. These systems are uniquely valuable targets because they’re rapidly evolving, can perform sensitive actions on behalf of users, and have large, diverse attack surfaces. You will play a crucial role in securing our agents by finding vulnerabilities that emerge from the interactions between the applications, infrastructure, tools, and models that power them. You’ll have the chance to not only find vulnerabilities, but actively drive their resolution, build reusable testing approaches, automate offensive security workflows with cutting-edge technologies, and use your attacker perspective to improve the security of OpenAI’s products. In this role you will: Conduct deep penetration tests of OpenAI’s agent-powered products, including web applications, APIs, cloud services, identity and authorization flows, CI/CD systems, and model-integrated product surfaces. Continuously hunt for exploitable vulnerabilities in the interactions between the appli
About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the role Our Sales team has a unique mission to help customers understand the deep impact that highly capable AI models can bring to their business and users. This role is a mixture of technical understanding, vision, partnership, and value-driven strategy. You’ll be a key driver of opportunities through the entire sales cycle, from pipeline generation to closure. You’ll work with researchers, engineers, and solution strategists to help customers evolve their industry with AI. This role is based in San Francisco. 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'll: Manage a portfolio of accounts, developing and executing strategies for a comprehensive account plan Lead our prospects’ journeys from consideration to successful deployment Partner with solutions and research engineering to build and execute complex customer programs and projects Own a consumption revenue target Manage consumption revenue forecasts Analyze key account metrics to create reports and provide insights to internal and external stakeholders Closely monitor the industry landscape (people, competitors, partners, etc.) to contribute to product roadmap and other corporate strategies Collaborate with solutions, marketing, communications, business operations, people operations, finance, product m
About the team The Applied AI Engineering team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and startups. We act as a trusted advisor and thought partner for our customers, working to build an effective backlog of GenAI use cases for their industry and drive them to production through strong technical guidance. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to late-stage startups. About the Role We are seeking a technically proficient, business-minded Applied AI 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, guiding them through ideation, development, delivery, and scaling to accelerate and maximize the value of what they build on our platform. You will have the opportunity to work on the most novel and creative use cases being built on our API, serving as a critical partner in collecting and delivering high-fidelity product and model feedback internally. You will collaborate closely with Sales, Solutions Engineering, Applied Research, and Product teams, and you will report to the Startups Applied AI Lead. This role is based in our San Francisco or New York offices. 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: Partner closely with strategic startup customers as their technical thought partner to build novel applications on our API, helping them rapidly move from ideation to scale. Provide proactive guidance to maximize business impact and accelerate application development. Experiment and prototype alongside customers, demonstrating practical use cases. Contribute to open-source resources and scale the function by sharing knowledge, codifying best practices, and publishing useful resources. Synthesize and deliver valuable feedback to the Product and Research
About the Team We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role OpenAI is looking for an experienced Performance Engineer to help us scale the performance, reliability, and efficiency of our systems. In this role, you'll apply deep technical expertise to optimize infrastructure and application-level performance across mission-critical products like ChatGPT and our developer API. You’ll work cross-functionally with teams building core services, training models, and developing real-time user experiences to push our latency, throughput, and cost-efficiency to the next level. We are looking for engineers who thrive in ambiguous environments, value deep systems understanding, and are motivated by delivering measurable impact. This is a highly technical, individual contributor role focused on root-cause analysis, profiling, instrumentation, and architecture-level performance improvements across our stack. In this role, you will: Analyze and optimize performance across application, middleware, runtime, and infrastructure layers—networking, storage, Python runtime, GPU utilization, and beyond. Develop tooling and metrics that provide deep observability into system performance. Collaborate closely with infra, platform, training, and product teams to identify key performance goals and drive systemic improvements. Influence architecture and design decisions to prioritize latency, throughput, and efficiency at scale. Lead investigations into high-impact performance regressions or scalability issues in production. Drive performance testing strategies and help define SLAs/SLOs around latency and throughput for critical systems. You might thrive in this role if you: Have 7+ years of experience in software engineering with a strong tr
About the Team At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure. The Caching Infrastructure team is responsible for building a caching layer that powers many critical use cases at OpenAI. We aim to provide a high-availability, multi-tenant cache platform that scales automatically with workload, minimizes tail latency, and supports a diverse range of use cases. We’re looking for an experienced engineer to help design and scale this critical infrastructure. The ideal candidate has deep experience in distributed caching systems (e.g., Redis, Memcached), networking fundamentals, and Kubernetes-based service orchestration. In This Role, You Will: Design, build, and operate OpenAI’s multi-tenant caching platform used across inference, identity, quota, and product experiences. Define the long-term vision and roadmap for caching as a core infra capability, balancing performance, durability, and cost. Collaborate with other infra teams (e.g., networking, observability, databases) and product teams to ensure our caching platform meets their needs. You Might Thrive In This Role If You: Have 5+ years of experience building and scaling distributed systems, with a strong focus on caching, load balancing, or storage systems. Have deep expertise with Redis, Memcached, or similar solutions, including clustering, durability configurations, client-side connection patterns, and performance tuning. Have production experience with Kubernetes, service meshes (e.g., Envoy), and autoscaling systems. Think rigorously about latency, reliability, throughput, and cost in designing platform capabilities. Thrive in a fast-paced environment and enjoy balancing pragmatic engineering with long-term technical excellence. About OpenAI OpenAI is an AI research and deployment company d
About OpenAI OpenAI is dedicated to ensuring that artificial general intelligence (AGI) benefits all of humanity. Our mission requires building not only world-class AI models, but also the infrastructure that enables those models to be deployed reliably, efficiently, and at global scale. As demand for AI continues to grow, we are expanding the ways OpenAI can bring high-performance inference capacity online across a diverse hardware ecosystem. About the Team The GPT Infrastructure team builds software that turns advanced inference and optimization research into production products. One focus is enabling strategic infrastructure partners and accelerator vendors to qualify and onboard new compute without a bespoke porting and optimization effort for every hardware platform. We build the control planes, APIs, secure partner-side execution environments, evaluation systems, artifact pipelines, and operational tooling that make these workflows repeatable and trustworthy. The work sits at the intersection of distributed systems, AI inference, compilers and runtimes, performance engineering, security, and external partnerships. About the Role We are seeking an experienced systems generalist who can work comfortably across the stack to help build an automated inference optimization platform. Given a workload, target hardware profile, compiler and runtime context, and a trusted verifier, the system runs durable optimization campaigns that generate, compile, execute, grade, and improve candidate kernels, runtime configurations, and serving-stack changes. You will design both the OpenAI-hosted control plane and the partner-side software that evaluates candidates on real accelerator hardware. The product must keep long-running workflows reliable, make performance results reproducible, and maintain clear trust boundaries around sensitive model and hardware information. This is a deeply cross-stack role, combining strong software engineering fundamentals with systems thinking and
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