Engineering Leader in United States

About the Team OpenAI's mission is to ensure that AGI benefits all of humanity. The Business Systems team helps make that mission possible by building the internal products and platforms that allow OpenAI to operate with speed, reliability, and care. We build internal applications and workflows for Finance and Supply Chain. Our work spans product discovery, React and TypeScript interfaces, Python services and APIs, data models, workflow orchestration, enterprise integrations, and the systems that connect people to systems of record. We work directly with the people who use these products and care about correctness, permissions, auditability, and production reliability. Examples of our work include building an integration platform for supply chain integrations, integrations with Oracle Fusion and Zip, contract intelligence applied to B2B revenue recognition, and Temporal-based agentic workflows for credit checks, duplicate bank detection, and invoice triaging. We turn these efforts into reusable patterns that can support many workflows, rather than one-off automations. About the Role We are looking for Product Engineers to build internal applications end to end. This role spans product discovery, user experience, frontend, backend services, data models, workflow orchestration, and integrations with order management, fulfillment, and supply chain systems. You will take a problem from a first conversation with a Finance or Supply Chain partner through design, implementation, rollout, and production support. Strong candidates combine product judgment with engineering depth. You should be comfortable moving between a React interface, a Python API, a durable workflow, and an integration with an enterprise system. You should be able to ship a useful first version quickly while building the foundations for reuse, security, and long-term maintainability. Direct AI experience is helpful, but the core requirement is strong product engineering judgment and reliable execution. I

About the Team OpenAI’s GTM Data Science team helps shape how our products are adopted, monetized, and scaled across organizations. We work at the intersection of Product, Go-to-Market, Finance, Research, and Data, turning product usage, customer evidence, and market signals into decisions that grow durable enterprise value. We’re looking for a senior Data Scientist to own the analytical strategy for enterprise knowledge-worker adoption. As ChatGPT Work and Codex become capable of research, analysis, document creation, spreadsheets, presentations, internal knowledge synthesis, and other agentic workflows, you will help determine how these products become embedded in everyday work—not merely tried once. About the Role You will define how we measure activation, retained usage, workflow depth, and value across ChatGPT Work, Codex, and connected enterprise systems. You will explain why adoption succeeds or stalls and identify the product, enablement, and commercial interventions most likely to create durable usage. This is a hands-on, zero-to-one role. You will work through imperfect telemetry, overlapping product surfaces, evolving definitions, and ambiguous business questions. You will partner closely with GTM, Product, Finance, Research, Customer Deployment, Analytics Engineering, and Data Science. Your work is successful when it changes a product, GTM, or investment decision. In This Role, You Will Define a trusted measurement framework for knowledge-worker adoption, including identity, eligible populations, activation, retained usage, penetration, workflow depth, feature adoption, and monetization. Map the knowledge-worker journey from initial exposure through first successful task, repeated workflows, multi-surface usage, and durable adoption. Identify which personas, functions, use cases, product capabilities, and account conditions are associated with deep and retained usage. Design and evaluate experiments and quasi-experiments across onboarding, enablement, wo

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. In the Model Experience team, we shape the default character and behavior of ChatGPT: how the model communicates, responds to users, uses its capabilities, and behaves across different contexts and languages. Our goal is to make every interaction with ChatGPT thoughtful, helpful, and trustworthy. We take an opinionated view of what good human–AI interaction should look like, then turn that vision into real model behavior through human data, evaluations, reward models, and post-training. Our work sits at the intersection of research, product, and model design. We partner closely with teams across OpenAI to conduct research and ensure our models are thoughtful, safe, reliable to serve millions of users. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research and the quality of human-AI interaction. 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: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modeling improvements. Design, implement, test, and debug code across our research stack. You might thrive in this role if you: Have a deep understanding of machine learning and machine learning applications. Have good judgment about model behavior and can communicate this judgment effec

About the Team OpenAI’s Cyber team works to make frontier AI safe, trusted, and transformative for developers and enterprises. This team is building the security foundation for Codex: the native controls that govern what Codex can access and do, and the interfaces that allow customers and security partners to inspect, constrain, approve, and respond to Codex activity. Our goal is to make Codex secure by default, governable by enterprises, and interoperable with the security products customers already trust . This extends the existing product direction around tenant-scoped tools, guarded actions, approval systems, and scalable partner interfaces. About the Role We are looking for a deeply technical Product Manager to help build Codex security controls and the partner ecosystem around them. This role focuses on securing Codex itself : how identity, permissions, tools, MCP servers, repositories, secrets, networks, and high-impact actions are governed across Codex products. You will also help define standard interfaces through which authorized customer and partner systems can provide security context, inspect activity, return policy decisions, receive telemetry, and initiate bounded responses. You will work closely with Codex product and engineering, OpenAI Security and Safety, enterprise customers, and partners across application security, identity, cloud security, data security, infrastructure, and security operations. In this Role you Will Build native security controls for Codex Partner with engineering, design, security, and safety teams to develop controls for: Identity, roles, permissions, and tenant isolation. Access to repositories, files, tools, MCP servers, secrets, networks, and infrastructure. Read, write, execute, and deployment authority. Human and policy-based approvals. Prompt-injection and untrusted-content defenses. Audit trails, provenance, stop conditions, revocation, and rollback. Help establish a graduated authority model in which local, read-only

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve people's lives. About the Role We are seeking a lead thermal simulation engineer to help accelerate the design and development of next-generation robotic systems through modeling, simulation, and analysis. You will work closely with mechanical, electrical, controls, and robotics engineers to evaluate designs before hardware is built, identify risks early, and guide critical architecture decisions. This role spans structural and thermal analysis and design across robotic subsystems including actuators, mechanisms, structures, electronics, and integrated systems. You will develop simulation workflows that improve engineering velocity, increase confidence in design decisions, and help us build more capable, reliable, and manufacturable robotic platforms. This role is based in San Francisco, CA. This role will be expected to be in office 4 days per week and offer relocation assistance to new employees. In this role, you will: Perform thermal simulations to assess heat generation, cooling strategies, thermal interfaces, and system-level thermal performance Partner with mechanical, electrical, and controls engineers to influence design decisions early in development Build simulation models to evaluate robotic actuators, transmissions, mechanisms, structures, soft goods, and integrated assemblies Correlate simulation results with physical testing and develop methodologies to improve model accuracy Support architecture trade studies by evaluating design concepts before hardware is built Develop simulation workflows, standards, and best practices that scale across the robotics o

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Stargate team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role The New Geography and International Growth Lead will own the strategy for infrastructure expansion into new geographies, including market assessment, stakeholder engagement, and coordination across energy, policy, commercial, and other infrastructure workstreams. This role identifies and enables priority international growth opportunities while ensuring alignment with regional regulatory, operational, sustainability, and long-term infrastructure objectives. This is an individual contributor lead role and does not have direct reports initially. The role will translate ambiguous market-entry questions into clear recommendations, identify the conditions required for OpenAI to advance in new regions, and coordinate the cross-functional work needed to turn priority geographies into executable infrastructure options. Key Responsibilities Build market-entry frameworks for international infrastructure geographies, including power availability, land readiness, regulatory posture, commercial fit, and execution risk. Assess priority regions and countries against OpenAI’s long-term compute, energy, sustainability, policy, and operational objectives. Coordinate cross-functional geographic diligence with energy, policy, commercial, legal, finance, procurement, engineering, and site-readiness stakeholders. Lead early stakeholder mapping and engagement strategy with utilities, regulators, government entities, developers, capital partners, and other market participants. Translate regional findings into exe

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Industrial Compute team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role Responsible for validating that proposed sites are buildable, compliant, and cost-effective. You will lead diligence across civil, geotechnical, environmental, and entitlement dimensions, identifying risks and driving mitigation strategies. Key Responsibilities Lead all technical diligence: geotech, soils, title/ALTA surveys, mineral rights, and access. Oversee permitting/entitlement path and schedule governance with agencies. Evaluate generator air permits, wetlands, floodplain, and stormwater constraints. Manage consultants performing feasibility studies and environmental assessments. Deliver go/no-go recommendations with risk and mitigation options. Build diligence templates and playbooks to scale future site reviews. Qualifications 8+ years in land development, civil/environmental engineering, or data center diligence. Knowledge of permitting, entitlements, and AHJ engagement. Strong project management and technical review skills. Experience managing consultants and interpreting complex studies. Regularly communicate site readiness updates, risks, and milestones to executive stakeholders Establish and track key performance indicators to assess the effectiveness of the site selection program and the contributions of external vendors and partners. About OpenAI OpenAI 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 depl

About the Team OpenAI’s Cyber team works to make frontier AI a decisive advantage for defenders. The Cyber Blue Team is an operator-led group focused on turning real defensive problems into better models, useful products, safe Codex workflows, and integrations with the security tools defenders already use. Our ambition is simple: Raise attacker cost. Lower defender toil. Prove it by defending OpenAI; scale it through the ecosystem. We are not setting out to build another SIEM or autonomous SOC. We want to build the AI reasoning and workflow layer that helps security teams investigate threats, create and validate detections, improve their controls, and respond with greater speed and confidence. About the Role We are looking for a Product Manager to help build a new generation of AI-powered cyber defense products. You will work closely with security practitioners, researchers, engineers, designers, internal security teams, customers, and technology partners to turn emerging model capabilities into products that solve meaningful defensive problems. This is an early-stage product role. The work will span product discovery, prototyping, evaluation, development, launch, and iteration. You will help the team identify where AI can create the most value for defenders and translate those opportunities into clear, usable, and trustworthy product experiences. Initial areas of focus may include: Detection engineering and detection-content development Threat hunting and investigation Security validation and control testing AI-agent and MCP runtime defense Integrations with security platforms and enterprise workflows Safe, governed assistance for incident response The specific roadmap will continue to evolve based on model progress, practitioner needs, internal learnings, and customer feedback. In This Role, You Will Work with security practitioners to understand high-value defensive workflows, recurring pain points, and opportunities for AI to materially improve outcomes. Help sh

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a

About the Team The Post-Training Frontiers team is responsible for training the frontier agents OpenAI ships to the world (GPT-Next). We train the flagship agentic models behind Codex, ChatGPT, and the API through large-scale reinforcement learning. The team’s work spans four areas. First, execution and science: working with teams across OpenAI to decide what can go into the final model and how, using scientific experiments and evals that are representative of the final pipeline so issues can be recognized early. Second, RL scaling: executing the final large-scale reinforcement learning run, making sure GPUs are used efficiently and training stays healthy. Third, research: improving horizontal capabilities like instruction following, factuality, memory, and multi-agent behavior, where the team’s broad visibility helps identify cross-cutting improvements across teams and domains. Fourth, engineering: maintaining the infrastructure stack and internal tools to ensure that both the final run and all integrations go as smoothly as possible and that the systems are easy to work with. About the Role This role focuses on keeping our frontier RL training runs fast, reliable, and unblocked. You will work across engineering and infrastructure problems as they emerge, from scaling and orchestration issues to inference bottlenecks, numerical problems, and hardware failures, as well as supporting large horizontal integrations in the big run, like multi-agent capabilities or memory. This is a role for a strong generalist who quickly learns anything needed for the task, has high attention to detail, debugs deeply, and is motivated by fixing the highest-impact problem in front of the team. In this role, you will: Keep large-scale async RL training runs moving by jumping into the most urgent engineering and infrastructure problems. Debug issues across training systems, inference, orchestration, scaling, and distributed infrastructure. Improve the reliability and efficiency of RL trai

About the Team The Account & Platform Integrity Operations team protects OpenAI’s ecosystem by ensuring that users, developers, partners, and organizations can access and build on our platform safely and responsibly. The team works across account integrity, fraud prevention, abuse detection, and platform risk to prevent bad actors from exploiting OpenAI’s products and developer surfaces. This role will sit within the Account & Platform Integrity Operations team while partnering closely with teams across the Ecosystem organization to ensure the platform can scale rapidly without compromising trust, quality, or safety. About the Role - Platform Operations Program Manager As OpenAI's developer ecosystem expands, we're building the operational foundation to support the next generation of plugins, MCP apps, agent skills, and integrations. As a Platform Operations Program Manager, you'll partner across Product, Engineering, Policy, Legal, Security, and Developer Experience to design the systems and operating models that enable ecosystem growth while maintaining quality, trust, and an exceptional developer experience. This role requires strong operational judgment, a deep understanding of developer platforms and APIs, empathy for the developer experience, and the ability to translate evolving product, platform, and policy requirements into scalable operational systems. Location: San Francisco, CA (Hybrid - 3 days in office) What You'll Do Own the operational processes that help developers bring apps, plugins, and integrations to market, from submission and review through launch, appeals, and ongoing monitoring. Manage external review partners and policy operations workflows, helping teams apply standards consistently while identifying areas where guidance, process, or quality expectations need to improve. Partner with Product, Engineering, Policy, Legal, Security, Developer Experience, and Go-to-Market teams to turn platform goals and requirements into clear, effec

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 As an Account Director focused on Strategic Banking you will own executive-level relationships with leading global banking institutions. You’ll help these organizations safely and effectively deploy OpenAI’s technology to transform customer experiences, modernize operations, enhance employee productivity, accelerate financial analysis, strengthen risk management, and unlock new AI-powered business capabilities. This role blends financial services expertise, technical depth, business acumen, and relationship-driven enterprise sales. You will collaborate closely with researchers, engineers, and financial services solution strategists to design secure, compliant, and high-impact AI deployments. This role is based in New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you’ll: Manage a focused portfolio of Strategic Banking accounts, developing long-term strategic account plans. Lead complex, multi-stakeholder sales cycles across business, technology, operations, and executive stakeholders. Partner with Solutions and Research Engineering to design pilots that demonstrate measurable business impact. Collaborate with compliance, privacy, security, and risk teams to ensure responsible deployment of AI in highly regulated environments. Own a revenue a

About the Team The Personal AGI team seeks to empower all of humanity to benefit from frontier intelligence in whatever way they choose. We are responsible for training models to deploy to millions of users globally via ChatGPT, the API, and future products. We aim to evolve ChatGPT from a chatbot to an infinitely capable and personalized superassistant supporting human flourishing. We work on defining, measuring, and improving capabilities across the training stack. Our focus areas include but are not limited to model behavior, personalization, safety, factuality, instruction following, personality, interactivity, multilingual fluency, world interaction, and bringing agents to everyone. We chart the course for what to strive towards. We partner closely with research and product teams across the company ensuring that our models are safe, efficient, and reliable. About the Role You’ll work as a Research Engineer / Scientist on the North Stars team within the broader Personal AGI research org. You will work on bringing the next generation of AI-enabled experiences to all of humanity by closing the capability overhang between power users and the average consumer, including areas like tool-use, feature discovery, connectors, and instruction following. You will think deeply about the current bottlenecks in model behavior, translate these insights into robust evals, training data, reward signals, and model and harness improvements. We're looking for individuals with strong ML engineering skills and research experience passionate about creative, product-driven research. 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: Own and pursue a research agenda to improve model capability and performance. Collaborate closely with the other research and product teams, allowing customers to optimize their own models. Build robust evaluations for tracking modelin

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 As an Account Director focused on Insurance you will own executive-level relationships with leading Insurance organizations. You’ll help these companies safely and effectively deploy OpenAI’s technology to accelerate financial data analysis, automate backend operations, drive AI-powered research, and personalize customer engagement. This role blends literacy, technical depth, business acumen, and relationship-driven enterprise sales. You will collaborate closely with researchers, engineers, and financial services solution strategists to design secure, compliant, and high-impact AI deployments. This role is based in New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you’ll: Manage a focused portfolio of Financial Services, specifically Insurance accounts, developing long-term strategic account plans. Lead complex, multi-stakeholder sales cycles. Partner with solutions and research engineering to design pilots that demonstrate measurable business impact. Collaborate with compliance, privacy, and security teams to ensure responsible deployment of AI in regulated environments. Own a revenue and consumption target; manage forecasts and pipeline reporting. Monitor industry and regulatory trends to guide customer and product strategy. Represent Ope

About the Team OpenAI, in close collaboration with our capital partners, is embarking on a journey to build the world’s most advanced AI infrastructure ecosystem. The Industrial Compute team is central to this mission, setting the core infra strategy and implementing this vision. From site selection to the buildout process, this team sits at the intersection of commercial, technical, strategy, and operations, interacting with teams and executives inside and outside of OpenAI. About the Role The Clean Energy and New Technology Lead will own infrastructure clean energy and emerging energy technology strategy and execution, identifying and deploying scalable solutions that enable resilient, low-carbon compute and data center growth. The role will work closely with regulatory and policy teams to align infrastructure expansion with OpenAI’s long-term environmental and operational objectives. This is an individual contributor lead role and does not have direct reports initially. The role will evaluate where emerging energy technologies can materially improve reliability, cost, carbon, speed, or resilience; translate those options into practical deployment pathways; and help ensure OpenAI’s infrastructure growth remains aligned with sustainability considerations. Key Responsibilities Evaluate emerging energy solutions such as clean firm power, advanced storage, grid flexibility, low-carbon backup power, heat reuse, water-related energy efficiency, and other scalable technologies where relevant. Identify pilot opportunities and deployment pathways that can move promising energy technologies from concept to commercially and operationally credible execution. Translate technical options into clear reliability, cost, schedule, carbon, regulatory, and operational implications for infrastructure decision-making. Partner with energy regulatory, policy, procurement, engineering, deployment, finance, legal, and site-readiness teams to align technology and sustainability choices with