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About the Team OpenAI’s Governance, Risk, and Compliance team helps ensure security and privacy are grounded in how our products and systems actually operate. Assurance Operations partners with Security, Engineering, Infrastructure, Product, Privacy, and Legal to make controls provable, risk decisions explicit, and audit readiness a result of well-designed systems. About the Role We are hiring a technical, product-minded GRC builder who can own consequential audits while improving the control and evidence systems behind them. You will build a reusable common control framework, use Codex to automate assurance work, validate changing system scope, and turn repeated audit friction into measurable improvements. We are looking for someone who questions inherited assumptions, solves novel problems creatively, works closely with engineers, and makes the next audit easier by improving the underlying system. You’ll be responsible for: Lead external, internal, customer, and certification audit work from scoping through evidence review, fieldwork, remediation, and closeout. Build a common control framework linking risk, control intent, implementation, owner, system, environment, evidence, and applicable frameworks. Validate actual scope and ownership instead of assuming last year's controls, product boundaries, or evidence remain accurate. Use Codex to build and test evidence checks, control mappings, request triage, owner workflows, monitoring, and remediation reporting. Partner with engineers on cloud architecture, identity, logging, data flows, software changes, vulnerabilities, and control effectiveness. Design maintainable, permission-aware tools that preserve source provenance, human review, and evidence integrity. Reduce repeated requests and operational burden for control owners through measurable workflow improvements. Define roadmaps, decision rights, milestones, success metrics, and clear cross-functional escalations. We’re looking for someone with: Direct ownership

About the Team The Applied AI team is responsible for ensuring the safe and effective deployment of Generative AI applications for developers and enterprises. 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. As the leader of our ADEs in the Large Enterprise segment, you’ll help companies transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models. About the Role We are seeking an Applied AI Engineering leader to ensure the technical success of our most strategic Large Enterprise customers across EMEA. In this role, you will manage the entire implementation journey, ensuring seamless platform integration. As the voice of our customers, you will align technical teams to deliver a consistent and exceptional experience throughout the customer lifecycle. Success will be measured by live production applications, increased API adoption, and impactful customer stories that demonstrate the value of our technology. This role is open in both our London and Munich 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: Own the strategy and operating model of the Large Enterprise Applied AI team, ensuring alignment with company objectives and the evolving needs of our customers. Lead, build, and mentor a team of high-performing ADEs to deliver exceptional customer outcomes, as demonstrated by production customer applications and increased API adoption. Serve as the technical advocate for our customers, synthesizing their needs to develop the Research and Applied Product/Engineering roadmaps. Act as the primary technical escalation point during development, fostering trust and maintaining direct communication with executive-level

About the Team The CoT Monitorability team at OpenAI studies whether and when the chain-of-thought of frontier reasoning models is monitorable enough to support scalable oversight. We study how to measure monitorability , which training mechanisms affect monitorability, and speculative methods to improve monitorability. While we mostly focus on CoT monitorability at the moment, we care more generally about any form of monitorability, auditing methods, and improving alignment. We were the first to show that chain-of-thought monitoring can be a practical additional safety mechanism, and today our monitoring systems are actively used on OpenAI’s largest RL training runs to detect misbehavior. The issues we surface are then used to help improve our reward functions, environments, etc (without directly training against a CoT monitor). Our work sits in Alignment and intersects with model training, alignment evaluations, monitoring, and frontier-risk research.We care most about monitorability where the stakes are high, and about preserving useful oversight signals as models become more capable. About the Role We’re looking for a researcher with strong empirical ML expertise and a deep interest in model behavior, alignment, or interpretability. Direct chain-of-thought interpretability experience is welcome but not required; strong candidates may come from broader interpretability, alignment, model training, or investigative model-behavior work. As a researcher on the Alignment team, you will design and run experiments that improve our understanding of model monitorability. You will investigate how training interventions across the model-development pipeline influence whether reasoning remains legible, build evaluations that make those questions measurable, and help translate findings into practical oversight and training recommendations. You may also help develop new monitoring models or methods and apply them to OpenAI’s largest training runs. This role is especially well

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, 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 OpenAI is seeking a Real Estate Lead to own land acquisition strategy and site-control execution for our next-generation data center portfolio across the U.S. This role sits at the front end of infrastructure delivery, translating market intelligence, broker/developer relationships, and commercial judgment into credible shovel-ready positions that meet OpenAI’s power, land, permitting, and expansion requirements. The Real Estate Lead will not operate as a traditional transactional real estate function. The scope is to help shape where OpenAI can build, secure the right land positions early, structure defensible commercial terms, and coordinate the legal, technical, and development work required to move opportunities from sourced lead to controlled site and ultimately to readiness handoff. This is an individual contributor lead role and does not have direct reports initially. The role also owns market prioritization and portfolio-level acquisition strategy across target geographies, and is expected to run multiple negotiations in parallel while translating site-control work into executive-ready acquisition recommendations. Key Responsibilities Own market prioritization and portfolio acquisition strategy across target geographies, including scenario analysis for speed, scale, expansion potential, and risk-adjusted economics. Proactively source and evaluate land parcels at scale to support long-term data center growth across priority markets. Build and manage a national pipeline of

About the Team OpenAI’s Education team is building products that advance how people learn with AI. The team works across higher education institutions, K-12 districts, and country-level partnerships, including applied research on how AI affects learning and cognitive outcomes. The team owns owns ChatGPT Edu, ChatGPT for Teachers, and related product/research work. The team partners closely with go-to-market, research, Consumer Learning, and model teams to turn education-specific insights into product experiences that can improve ChatGPT more broadly. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the Role We’re looking for a hands-on Tech Lead Manager to lead and manage a team of senior full-stack engineers building AI-native learning experiences in ChatGPT. This person will combine technical execution, product judgment, and people leadership: they will write and ship code, manage engineers, and help shape the product direction for how students and Educators use AI. In This Role, You Will Lead and manage a team of three senior full-stack engineers. Build product experiences for ChatGPT Education, ChatGPT for Teachers, and AI-native learning workflows. Partner with research teams on field studies, randomized control trials, classifiers, data pipelines, and cognitive-outcome measurement. Collaborate with Consumer Learning and model teams to translate education insights into broader ChatGPT behavior and product improvements. Drive execution across product, engineering, research, go-to-market, and partner teams. Help define product strategy, priorities, and delivery plans for a new product pod. You Might Thrive In This Role If You Have several years of direct people-management experience with engineers. Are still highly technical and comfortable doing IC engineering work. Have strong pr

About the Team The Industrial Compute team is responsible for building the physical infrastructure that powers OpenAI’s largest-scale AI systems. We design, deploy, and operate next-generation compute infrastructure across a rapidly expanding global footprint, combining OpenAI-owned infrastructure with strategic cloud and infrastructure partners to support frontier AI workloads. As our infrastructure footprint grows, operational excellence across third-party providers becomes increasingly critical. Our team ensures external infrastructure partners consistently deliver the reliability, performance, and operational maturity required to support OpenAI’s rapidly expanding compute environment. About the Role We are seeking a Hardware Technical Program Manager, Infrastructure Partner Operations to lead operational delivery across OpenAI’s third-party infrastructure partners, including major cloud service providers and strategic compute vendors. In this role, you will serve as the primary operational program manager for external infrastructure partners, driving accountability for service delivery, operational readiness, incident management, performance reporting, and continuous operational improvement. You will work closely with partner engineering and operations teams while coordinating internally across Hardware Engineering, Infrastructure Operations, Capacity Planning, Networking, Supply Chain, Deployment, Reliability Engineering, and executive leadership. Success in this role requires someone who understands how hyperscale infrastructure organizations operate, can establish strong operational governance with external partners, and is comfortable driving complex technical programs without direct ownership of the underlying infrastructure. Key Responsibilities Own operational engagement with third-party infrastructure providers, ensuring consistent execution against operational commitments, service-level agreements (SLAs), and performance expectations. Develop operationa

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 is evaluating multiple infrastructure pathways, including powered land, colo/BTS, and NeoCloud opportunities. The Site Readiness & Development team provides the diligence layer needed to compare opportunities, identify risk, and support credible deployment decisions across those pathways. About the Role The NeoCloud & Colo Due Diligence Lead will evaluate third-party infrastructure opportunities where OpenAI is considering deployment through NeoCloud, colo, or BTS structures. This role will focus on facility and deployment readiness, including MEP readiness, rack strategy, developer capability, facility design, power deliverability, schedule credibility, and operating assumptions. Unlike the land diligence team, this role is centered on technical and operational readiness of third-party infrastructure rather than greenfield site master planning, civil development, and entitlement strategy. This is an individual contributor lead role and does not have direct reports initially. The role determines whether each opportunity is fit-for-use and fit-for-service against OpenAI facility, rack, power, network, reliability, and operational standards; identifies material deficiencies and tracks remediation with developers/operators; and evaluates commissioning, validation, AHJ/code, and deployment interfaces such as structured cabling, network readiness, and high-density rack support where relevant. Key Responsibilities Lead diligence on NeoCloud, colo, and BTS opportunities across technical and operational readiness dimensions. Assess each opportunity against OpenAI facility, rack, power, network, reliability, and operational standards to determine deployment fit. Validate MEP readiness, rack deployment strategy, facility design assumptions, power deliverability, and schedule credibility. Identify material deficiencies and work with developers/operators to define remediation plans, owners, timing, and residual risk. Review reliability, availabilit

About the Team OpenAI’s API Platform organization builds the products and infrastructure that help first-party and third-party developers build with OpenAI models. We ship the API primitives, tools, SDKs, documentation, playgrounds, and platform experiences that make OpenAI’s capabilities reliable, understandable, and useful in production. The API Experience team is focused on the end-to-end developer experience for the OpenAI API. We own the surfaces developers touch every day: docs, SDKs, the Playground, examples, onboarding flows, and the systems that help developers go from first request to production deployment quickly and confidently. About the Role We’re looking for full stack and frontend engineers to help define and build the next generation of OpenAI’s developer experience. In this role, you’ll work across frontend product surfaces, backend systems, SDK and documentation pipelines, and API workflows that serve millions of developers and companies. You’ll partner closely with product, design, research, API engineering, and developer-facing teams to make complex AI capabilities simple to understand, easy to test, and safe to launch in real-world applications. This is a highly cross-functional role for someone who cares deeply about craft, developer empathy, reliability, and product velocity. In this role, you will: Build and scale developer-facing products including the OpenAI API Playground, documentation experiences, onboarding flows, examples, and API workflow tools. Own full stack projects end to end, from product definition and UX collaboration through backend implementation, launch, measurement, and iteration. Improve the systems that generate, maintain, and publish SDKs, API references, docs, guides, and developer examples. Partner with API, research, design, and infrastructure teams to bring new model capabilities and API primitives to developers in a clear, usable way. Use developer feedback, product analytics, and direct customer insight to identif

About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. This role sits on a new team within USRO focused on building operational capacity for new, ambiguous, or fast-moving areas of work. The team helps define what needs to be built, creates the operating model to support it, and works with partner teams to make the work scalable and durable over time. As a Strategic Operations Lead, you will focus on large, cross-functional initiatives that require clear thinking, technical fluency, strong execution, and the ability to bring structure to undefined problems. About the Role We are seeking a Strategic Operations Lead to drive new and existing strategic operating builds across User Safety & Risk Operations. This is a senior IC role for someone who can turn broad, undefined priorities into clear operating models, launch plans, requirements, stakeholder alignment, documentation, reporting, and execution rhythms. This role will often support initiatives where OpenAI is developing new products or partnerships and the operating model is still being defined. These programs have a direct user safety and risk nexus because new deployment models can change what signals OpenAI can see, who owns response decisions, and how user-impacting risks are detected, escalated, and resolved. You will clarify what OpenAI owns, what partner teams own, what signals we can reliably monitor, how issues should be escalated, and how the workflow should evolve from launch support into a durable operating model. The right person is highly strategic and deeply practical. They can move from executive-level framing to detailed workflow design, stakeholder management, SOPs, launch readiness, ri

About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. Make a Difference: Monitor and maintain deployed m

About the Team Our London-based team builds the backend systems that help ChatGPT scale reliably. We work on infrastructure close to the product, partnering with engineering teams to improve the performance, resilience, and operability of critical user-facing systems. Our work combines backend software engineering with distributed systems and production reliability. We build shared capabilities, improve high-traffic workflows, and make it easier to introduce new product functionality without compromising performance or availability. About the Role This role is for software engineers who want to build and evolve backend systems operating at significant scale. You’ll write production code, design shared infrastructure, and solve technical challenges involving performance, distributed systems, and system reliability. You’ll also own how those systems behave in production: how changes are rolled out, how issues are detected and diagnosed, and how recurring operational problems can be addressed through better software and system design. This is a strong fit for backend engineers who enjoy complex systems problems and want a direct connection between the infrastructure they build and the experience of ChatGPT users. In this role, you will: Design, build, and maintain backend systems supporting high-traffic ChatGPT experiences. Develop shared services, APIs, and infrastructure that help product teams build and launch new capabilities safely. Improve the performance, scalability, and efficiency of production systems as usage and product complexity grow. Build and improve systems for asynchronous processing and other large-scale backend workloads. Lead architectural improvements and infrastructure migrations while maintaining correctness, compatibility, and safe rollout and rollback. Strengthen monitoring, alerting, and diagnostics to detect problems early and reduce customer impact. Participate in on-call, incident response, and root-cause analysis, and turn operational lea

About the Team OpenAI's Strategic Sourcing team helps the company scale responsibly, efficiently, and at speed. We partner with leaders across Engineering, Research, IT, Systems, Finance, Legal, and other teams to shape commercial strategies, negotiate critical agreements, and build resilient supplier ecosystems. Our work connects technical strategy, commercial judgment, financial discipline, and execution in support of OpenAI's mission. About the Role OpenAI is seeking a Strategic Technology Negotiations Lead to personally lead some of the company's most complex and consequential technology negotiations. This is not a people manager role. It is a senior strategic IC operator role for an expert negotiator who wants to remain close to the work and personally drive high-impact outcomes. We are especially interested in leaders who have managed teams and are intentionally seeking an individual contributor role where their impact comes through judgment, influence, and direct ownership. Rather than owning a fixed category, you will be deployed against high-priority opportunities where deal complexity, commercial stakes, executive visibility, or time pressure require exceptional negotiation leadership. Your initial focus will include data platforms and infrastructure, including data lake and lakehouse technologies, observability, and enterprise SaaS, with flexibility to work across other strategic technology areas. You will lead negotiations from strategy through execution, aligning decision-makers and driving agreements to closure. Many of these negotiations exist within broader supplier and partner ecosystems. You will look beyond the immediate transaction to account for interconnected cost, equity, revenue, partnership, risk, and long-term strategic implications. Success requires strong economics, sound judgment under pressure, executive credibility, and the ability to bring stakeholders with you through difficult decisions. This role is based in San Francisco, CA. We u

About the team OpenAI’s Forward Deployed Engineering (FDE) team partners with global pharma and biotech, CROs, and research institutions to deploy production-grade AI systems across the R&D value chain. We operate at the intersection of customer delivery and core platform development, converting early deployments into repeatable system standards and evaluation practices that scale across regulated environments. About the role As a Life Sciences FDE Manager, you’ll lead a team of FDEs delivering production AI systems across drug discovery and development workflows. You’ll own delivery outcomes and team leverage while staying hands-on as a player-coach. This includes building and shipping alongside the team, setting technical direction, and maintaining a high bar for production-grade systems in regulated environments. We measure success through the health and quality of your FDE team, production adoption and measurable workflow impact, the quality of eval-driven feedback delivered back to Product and Research, and the repeatability of deployment patterns across life sciences customers. This role is based in New York City We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. This role will require travel up to 25%. In this role you will Lead and grow a team of FDEs delivering production AI systems across regulated life sciences environments Be accountable for your team’s end-to-end delivery outcomes, balancing scope, speed, robustness, and risk in high-stakes deployments Coach and develop engineers through direct feedback, high technical standards, and clear expectations for execution and ownership Operate as a player-coach, directly contributing to production systems while leading, coaching, and setting technical direction Guide teams through ambiguous, multi-workstream engagements spanning data, workflows, infrastructure, security, and scientific stakeholders Run evaluation loops that measure model and system quality against