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About the Team The Employee Technology & Experience (ETX) team is responsible for delivering a world-class internal technology experience that enables employees to do their best work. We support and operate the employee-facing systems that keep the company moving quickly and efficiently. ETX spans support, logistics, AV, identity, endpoints, SaaS administration, automation, enterprise tooling, and internal infrastructure operations. We partner closely with Security, Engineering, Workplace, Finance, People, and other teams to keep OpenAI’s internal technology reliable, scalable, and moving at the pace of the company. About the Role We are hiring a Program Manager to help scale how IT operates across OpenAI. This role will lead complex cross-functional programs that improve operational maturity, streamline how teams work together, and turn high-impact initiatives into durable operational capabilities. You will work across IT, Security, Engineering, Workplace, and other functions to drive alignment, remove friction, and help build the operational foundation needed to support OpenAI’s rapid growth. You’ll be responsible for: Lead cross-functional operational programs that improve scalability, consistency, and operational maturity. Drive operational excellence initiatives across IT Support, employee lifecycle operations, meeting room and calendaring services, onsite support, vending, and research support environments. Build operating models, readiness plans, escalation paths, governance cadences, and success metrics for complex operational programs. Partner with technical teams to ensure new deployments, infrastructure investments, and internal platforms are operationally ready and sustainably supported at scale. Drive high-priority operational programs supporting company growth, including infrastructure expansion, operational integrations, and other emerging initiatives. Improve operational visibility, stakeholder alignment, and coordination across long-running cros

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. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. 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. 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 a working knowledge of relevant models, and building evaluations for model capability improvement. Are comfortable diving into a large ML codebase to debug. Thrive in a dynamic and technically complex environment. 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 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

About the Team The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. We support critical domains across identity, access, infrastructure security, enterprise systems, and internal productivity. As OpenAI grows, audit readiness and control assurance increasingly depend on reliable data: accurate system inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. Our goal is to move beyond manual evidence collection and build scalable data products, automated validation, and continuous control monitoring that make security and IT controls measurable, repeatable, and defensible. About the Role We are looking for an IT Controls Data Engineer to build the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. In this role, you will design and maintain the pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to turn complex system behavior into reliable control data products. This is a technical builder role. The ideal candidate is strong in data engineering and analytics engineering, comfortable working with enterprise and security system data, and able to explain data lineage, source-system behavior, and control logic clearly to technical and audit stakeholders. You’ll be responsible for Building reliable data pipelines, models, and datasets for IT controls, including access, identity, configuration, change, ticketing, exception, and evidence data. Creating data quality, lineage, reconciliation, and completeness checks that make control data defensible for SOX and other audit use cases. Designing automated evidence generation workflows that produce compl

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. About the Role As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments , subscriptions , and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally. 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 checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency. Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible. Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action. Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality. You might thrive in this role if you have 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments Fluency in SQL and Python ,

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods. This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact. 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. Responsibilities Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning. Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluati

About the Team The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls. Our work spans data inventory and mapping, classification and lineage, retention and deletion, access governance, purpose and usage controls, auditability, and lifecycle automation. We aim to make policy-aligned data handling the default while giving teams clear, reliable primitives for building and operating products at scale. About the Role We are looking for an experienced Software Engineer to drive the architecture and execution of user data governance across OpenAI. You will define technical direction, build shared platforms and controls, and lead cross-functional programs that make data flows discoverable, policies enforceable, and ownership explicit. This role is well suited to a senior engineer who can move between deep systems design and organization-wide influence, turn ambiguous requirements into pragmatic roadmaps, and operate high-trust systems end to end. This position is based in San Francisco. Relocation assistance is available. In this role, you will: Set the technical strategy and architecture for user data governance across data mapping, classification, lineage, retention, deletion, access, and permitted usage. Design and build shared services, APIs, metadata systems, and policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable. Establish reliable inventories of user data, system ownership, data flows, and policy applicability across products, infrastructure, analytics, and research systems. Partner with Product, Data, Infrastructure, Security, and Legal leaders to define decision rights, translate requirements into controls, and drive adoption across teams. Own governance systems

About the Team The Core Services team is responsible for building and managing foundational services. It acts as the bridge between core infrastructure (e.g. compute, storage, networking) and product engineering teams, and enables product teams to move fast, build reliably, and scale efficiently. About the Role As a software engineer in the core services team, you will design and operate critical backend platforms such as caching systems, workflow orchestration, metadata stores, and file services. You’ll focus on building highly reliable, scalable, and performant systems that serve as the backbone of our products. We’re looking for people who are passionate about building infrastructure that empowers product teams, love working on distributed systems challenges, and enjoy creating well-designed APIs and abstractions that accelerate development. 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, build, and maintain shared infrastructure services such as caching layers, workflow orchestration (Temporal), metadata stores, and file storage services. Collaborate with product teams to provide scalable, reliable primitives that abstract the complexities of distributed systems. Improve performance, resilience, and scalability of core services that power customer-facing applications. You might thrive in this role if you: Have experience with distributed systems, caching infrastructure (e.g., Redis, Memcached), metadata storage (e.g., FoundationDB), or workflow orchestration (e.g., Temporal, Cadence). Have experience running containerized services in cloud environments and integrating them into automated build/test/release (CI/CD) workflows. Understand trade-offs in consistency models, replication strategies, and performance optimization in multi-region systems. Excel at communication and collaboration with cross-functional teams, and are obsesse

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for a Backend Software Engineer to help architect and scale the infrastructure that powers our knowledge systems. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. In this role, you will: Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. Collaborate closely with product, research, and engineering teams to integrate OpenAI mode

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside leading cloud providers, engineering firms, construction partners, utilities, and equipment manufacturers, we are delivering hyperscale AI campuses that enable the next generation of frontier AI models. The Strategic Sourcing team develops and executes the commercial strategies that ensure our infrastructure programs have reliable access to the equipment, materials, and strategic partners needed to deliver at unprecedented scale. We partner closely with Infrastructure Delivery, Capacity Planning, Design Engineering, Hardware Operations, Finance, Legal, and our external suppliers to build a resilient global supply network capable of supporting Industrial Compute's long-term growth. As we continue expanding globally, strategic sourcing becomes a critical competitive advantage, ensuring our infrastructure programs remain cost-effective, resilient, and capable of executing against aggressive deployment timelines. About the Role We are seeking a Strategic Sourcing Manager, Data Center Infrastructure to lead sourcing strategy for the critical infrastructure systems that power Industrial Compute campuses. This role will develop commercial strategies, negotiate strategic supplier agreements, and manage relationships across engineering, construction, manufacturing, and infrastructure partners responsible for delivering mission-critical facilities. You will work closely with Infrastructure Delivery, Capacity Planning, Engineering, Finance, Construction, and external suppliers to ensure Industrial Compute has the capacity, supplier relationships, and commercial frameworks required to support rapid global expansion. The ideal candidate has experience sourcing major infrastructure systems for hyperscale data centers, mission-critical facilities, industrial construction, semiconductor manufacturing, energy infrastructure, or similarly comple

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 the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a

About the Team OpenAI's Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside leading cloud providers, engineering firms, construction partners, utilities, and equipment manufacturers, we are delivering hyperscale AI campuses that enable the next generation of frontier AI models. The Strategic Sourcing team develops and executes the commercial strategies that ensure our infrastructure programs have reliable access to the equipment, materials, and strategic partners needed to deliver at unprecedented scale. We partner closely with Infrastructure Delivery, Capacity Planning, Design Engineering, Hardware Operations, Finance, Legal, and our external suppliers to build a resilient global supply network capable of supporting Industrial Compute's long-term growth. As we continue expanding globally, strategic sourcing becomes a critical competitive advantage, ensuring our infrastructure programs remain cost-effective, resilient, and capable of executing against aggressive deployment timelines. About the Role We are seeking a Strategic Sourcing Manager, Data Center Infrastructure to lead sourcing strategy for the critical infrastructure systems that power Industrial Compute campuses. This role will develop commercial strategies, negotiate strategic supplier agreements, and manage relationships across engineering, construction, manufacturing, and infrastructure partners responsible for delivering mission-critical facilities. You will work closely with Infrastructure Delivery, Capacity Planning, Engineering, Finance, Construction, and external suppliers to ensure Industrial Compute has the capacity, supplier relationships, and commercial frameworks required to support rapid global expansion. The ideal candidate has experience sourcing major infrastructure systems for hyperscale data centers, mission-critical facilities, industrial construction, semiconductor manufacturing, energy infrastructure, or similarly comple

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 peoples’ lives. About the Role We are hiring a Sim Infrastructure Engineer to turn simulation systems into reliable, automated, production-quality pipelines that power model training, evaluation, and hardware-in-the-loop validation. This role owns the automation, orchestration, and tool integration that apply simulation to concrete robotics tasks: building CI/CD for SIL/HIL, presubmit checks, automatic model evaluation, metric computation and reporting, and the runtime infrastructure to run simulations at scale. You will collaborate closely with Sim Realism, Sim Environments, Research, and Ops to make simulation an integrated, reproducible, and measurable part of our ML and robotics workflows. This role is based in San Francisco, CA, and requires in-person 4 days a week. In this role, you will: Build and maintain presubmit checks, continuous integration and deployment pipelines for simulation code, environments, and tasks so simulation artifacts are testable, versioned, and reproducible. Implement end-to-end automation to run model evaluation in sim (SIL) and orchestrate HIL runs; compute realism and task metrics, generate dashboards and alerts, and ensure evaluation is repeatable and auditable. Create robust APIs and connectors so research, training, and data-collection systems can schedule, seed, and evaluate batches of simulations; support RL rollouts, imitation-data collection, and presubmit model checks. Build scheduling, batching and orchestration for running very large numbers of concurrent rollouts (target tens of thousands of rollouts / large RL workloads), sol

About the Team IT Systems Operations serves as the operational control layer connecting Security, Engineering, and Employee Technology platforms. The team ensures employee-facing systems, identity workflows, and enterprise applications operate in a predictable, governed, and continuously reliable manner as the organization scales. Beyond implementation, the team establishes structured operating patterns that ensure platform changes, access models, integrations, and lifecycle workflows evolve safely and consistently across the enterprise environment. About the Role This role acts as an operational owner for identity-connected enterprise SaaS platforms and system change controls supporting OpenAI’s compliance requirements. The engineer will be responsible for ensuring that production configuration, access models, and platform changes remain compliant, auditable, and consistently operated through defined controls. You will own and operationalize controlled system and workflow changes across identity platforms, SaaS applications, collaboration tooling, and enterprise infrastructure. You will partner closely with Security, Platform Engineering, and IT Support Operations to: Ensure identity and access workflows behave consistently across systems Implement structured rollout and configuration practices for enterprise applications Improve visibility and traceability of system changes impacting employee workflows Translate operational requirements into durable automation and policy-aligned implementations Success in this role requires not only strong engineering capability, but also sound operational judgment, disciplined documentation practices, and effective cross-functional collaboration. In this role, you will: Enterprise SaaS & Identity Platform Ownership Own administration and operational stewardship of enterprise SaaS and identity-connected platforms, ensuring configuration integrity, access governance, and compliance with defined control requirements. Own onboard

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Learn more about OpenAI’s approach to safety. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. About the Role At OpenAI, we're dedicated to advancing artificial intelligence, and we know that creating a secure and reliable platform is vital to our mission. That's why we're seeking a software engineer to help us build out our trust and safety capabilities. In this role, you'll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You'll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner. Your Responsibilities: Architect, build, and maintain anti-abuse and content moderation infrastructure designed to protect us and end users from unwanted behavior. Work closely with our other engineers and researchers to utilize both industry standard and novel AI techniques to measure, monitor and improve AI models’ alignment to human values. . Diagnose and remediate active incidents on the platform and build new tooling and infrastructure that address the root causes of system failure. You might thrive in this role if: You have built and run production services in a high growth, rapidly scaling environment. You can debug live issues and restore systems quickly. You have worked on content safety, fraud, or abuse, or are motivated and excited to work on present-day (“now-term”) AI safety. You have experience with Python or with modern languages such as C++, Rust, or Go, and are able to quickly ramp up on Py