Support Team Lead in United States

About the Team Our Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. Within Safety Systems, the Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. About the Role Frontier AI systems are rapidly expanding what is possible in cybersecurity and software engineering. These capabilities create major defensive opportunities, but they also raise serious dual-use and misuse risks across areas such as malware development, exploit discovery, vulnerability chaining, credential abuse, cyber intrusion, and autonomous offensive operations. In this role, you will help define how OpenAI’s models should behave in high-risk cybersecurity contexts. You will develop policy frameworks, threat models, taxonomies, evaluations, and behavioral specifications that guide model behavior across training, deployment, and monitoring systems. This role sits at the intersection of cybersecurity, AI safety, threat modeling, evaluation science, and policy implementation. You will work closely with research, engineering, safety training, preparedness, and product teams to build policies that are technically grounded, measurable, enforceable, and responsive to real-world cyber risk. Your Responsibilities: Design and maintain model policies for cybersecurity and frontier-risk domains, especially dual-use and high-risk cyber capabilities. Translate cybersecurity threat models into clear behavioral specifications, evaluation criteria, grading guidance, and system-level mitigations. Define practical boundaries between legitimate security research, defensive workflows, and assistance that could materially enable harmful activity. Build policy artifacts that support i

About the Team The Stargate organization is responsible for building and scaling the physical infrastructure systems that power OpenAI’s next generation of AI training and inference platforms. This includes the manufacturing, deployment, and operational execution required to bring large-scale compute infrastructure online globally. The team operates at the intersection of data center infrastructure, hardware manufacturing, supply chain, deployment operations, and systems planning. We partner closely across Infrastructure Strategy, Manufacturing Operations, Capacity Planning, Supply Chain, Deployment, and Engineering to execute one of the largest infrastructure scale-outs in the industry. About the Role We are seeking a Technical Program Manager, Rack Delivery to drive operational execution across rack manufacturing, site readiness, and deployment coordination for Stargate infrastructure programs. This role will serve as a key connective layer between manufacturing partners, deployment teams, and infrastructure readiness programs to ensure rack production and delivery timelines remain aligned with site availability and deployment sequencing. You will help manage operational execution across contract manufacturers (CMs), support build planning and RCCA processes, and coordinate deployment readiness across multiple concurrent infrastructure programs. You will also partner closely with Demand Planning teams to translate strategic planning inputs into actionable SKU-level manufacturing and delivery schedules. This role is ideal for someone who thrives operating across ambiguity, manufacturing operations, infrastructure deployment, and large-scale cross-functional execution. 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 support. Key Responsibilities Drive cross-functional coordination between rack manufacturing, deployment operations, and site readiness programs. Manage operational execution acros

About the Team The Youth Well-Being product team is part of the Integrity pillar at OpenAI, responsible for ensuring that our state-of-the-art AI technologies are deployed in safe, age-appropriate, and beneficial ways—especially for youth and families. We work across OpenAI’s entire product surface area, from ChatGPT to future-facing tools, to architect safety and trust into the foundation of our systems. Our mission: empower families while meeting the highest standards of regulatory compliance and ethical responsibility. This work is core to OpenAI’s mission to ensure AGI benefits all of humanity. Safety, especially for the most vulnerable users, is more important to us than unfettered growth. About the Role We’re looking for a Senior Software Engineer to help architect and build the foundational systems that power family- and youth-facing experiences at scale. You’ll help define how teens and guardians engage with OpenAI products—ensuring those experiences are safe, compliant, and empowering. You’ll operate across a broad technical surface: building identity primitives, age assurance pipelines, and guardian tools that support both proactive and reactive interventions. You’ll collaborate closely with a cross-functional team of engineers, data scientists, designers, user researchers, and policy experts. This is a high-impact, 0→1 opportunity to set the standard for how families interact with generative AI. In this role, you will: Architect and implement teen and guardian experiences across OpenAI products, including ChatGPT. Build global age assurance systems that are privacy-preserving and tailored to regional compliance needs. Design and evolve our identity infrastructure to support scalable, secure, and resilient user journeys at consumer internet scale. Help define safety and well-being metrics, and continuously improve user trust through technical interventions. You might thrive in this role if you: Have built products or infrastructure for users under 18, or h

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

About the Team Equity Administration at OpenAI is responsible for the operational foundation of our equity programs. Our team ensures equity data and reporting are reliable, our systems and integrations are resilient, and our processes and controls are built to scale globally. We work cross-functionally with Legal, Finance/Accounting, Payroll, Tax, People, and key vendors to uphold compliance requirements and enable equity strategy as the company evolves. About the Role We’re looking for an experienced Manager, Global Equity Administration to help run our global equity programs with a focus on high-quality execution, scalable processes, auditable controls, and reliable equity systems. You will be hands-on in day-to-day equity administration and help improve how we operate as we scale. You will report to the Head of Equity Administration and partner closely with Legal, Equity Programs, Compensation, Tax, Payroll, and Finance to ensure equity operations are accurate, timely, and employee-friendly. Location: 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: Execute end-to-end employee equity administration across key lifecycle events (new grants, vesting/RSU releases, option exercises, and related transactions). Run recurring operational cycles by managing timelines, checklists, stakeholder inputs, and issue resolution. Produce audit-ready equity reporting and support accounting, compliance, and reporting needs with accurate, well-documented data. Build and maintain automated reporting (scheduled reports, dashboards, reconciliations) to reduce manual effort and improve speed and accuracy. Support equity system operations (Shareworks or comparable) including troubleshooting, configuration updates, permissions, report builds, and workflow maintenance. Partner with Internal Controls to keep process documentation, narratives, and flowcharts current,

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 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 software engineer on the Scaling team, you’ll help build and optimize the low-level stack that orchestrates computation and data movement across OpenAI’s supercomputing clusters. Your work will involve designing high-performance runtimes, building custom kernels, contributing to compiler infrastructure, and developing scalable simulation systems to validate and optimize distributed training workloads. You will work at the intersection of systems programming, ML infrastructure, and high-performance computing, helping to create both ergonomic developer APIs and highly efficient runtime systems. This means balancing ease of use and introspection with the need for stability and performance on our evolving hardware fleet. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Design and build APIs and runtime components to orchestrate computation and data movement across heterogeneous ML workloads. Contribute to compiler infrastructure, including the development of optimizations and compiler passes to support evolving hardware. Engineer and optimize compute and data kernels, ensuring correctness, high performance, and portability across simulation and production environments. Profile and optimize system bottlenecks, especially around I/O, memory hierarchy, and interconnects, at both local and distributed scales. Develop simulation infrastructure to validate runtime b

About the Team The Fleet team builds core components to enable productive research from small to state of the art scale across OpenAI, with the goal of accelerating progress towards AGI. We frequently collaborate with other teams to speed up the development of new state-of-the-art capabilities. About the Role As we scale up with more researchers and engineers joining OpenAI, we seek a pragmatic and passionate engineer with a strong focus on the development experience for both engineers and scientists. In this role, you will be responsible for building and maintaining systems that allow our research + engineering organization to iteratively develop, test, and deploy new features reliably, with high velocity, and with a frictionless and fast development cycle. You will help oversee and drive to the vision of how we should build, test and deploy software. You will drive the design of our continuous integration pipelines, testing infrastructure, training and support around our build system. Our current environment relies heavily on Python, Rust, and C++, which you will take ownership of and strive to transform into a state of the art development experience for research. Ultimately, your role will be to provide the necessary tools and metrics to support our fast-paced culture and ensure a stable, scalable platform for growth, while also fostering a seamless and low friction experience for OpenAI’s research. This role is based in San Francisco, CA. For a San Francisco role, we use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You might thrive in this role if you: Have supported large monorepo development and deployment before Are a proficient Python programmer working in large monorepos Are proficient with Docker and Kubernetes Experienced in CI/CD 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 boun

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 The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software is reliable, testable, and ready to ship. We design and maintain automated test frameworks, hardware-in-the-loop labs, and release pipelines that keep quality signals trustworthy and enable rapid, safe product launches. Our work spans developer tools, automation, systems integration, and cross-team collaboration to ensure every release meets the highest standards. About the Role As a Software Engineer, Quality and Developer Tools , you will build and own the systems that validate our device software—from test frameworks and regression infrastructure to hardware-in-the-loop labs and release gates. You’ll design the tooling and automation that keep quality signals trustworthy, integrate them into CI/CD, and make it easy for engineers and QA vendor technicians to execute reliable, repeatable workflows. We’re looking for engineers with deep experience in software quality, automation, developer tooling, and hardware-software integration who thrive on building scalable, reliable systems for validation and release readiness. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Test infrastructure & frameworks: Design, implement, and maintain a unified test framework for device software across unit, integration, system, and end-to-end testing, with reproducible runs and integrations with GitHub, Linear, and Slack. CI/CD integration & releases: Integrate test suites with Buildkite, enforce promotion criteria for staging and production, auto-file regressions, and publish traceable artifacts and release notes. Hardware-in-the-loop lab design & orchestration: Plan and bring up racks, power and networking systems, and orchestration for device testing; support automated flashing, provisioning

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 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 As a Security Engineer you will join our OpenAI engineers and researchers in building, operating and securing transformational AI technologies. This role will focus on all aspects of Detection & Response but with a strong emphasis on detecting insider threats and influencing controls to safeguard OpenAI's most sensitive assets. In this role, you will: In this role, you will: Innovate on Detection and Response infrastructure to engineer and automate end-to-end detection and investigation workflows. Develop, measure, and tune detection rules to ensure effective and sustainable operations. Drive projects across OpenAI’s technology stack with a focus on insider threats, ranging from access abuse and intellectual property theft to novel risks emerging within AI infrastructure. Partner closely with cross-functional stakeholders, including HR, Legal, and peer investigative teams, providing technical expertise and evidence to support investigations. Collaborate on cutting-edge AI research, and use AI to improve OpenAI’s Security posture. You might thrive in this role if you: 5+ years experience working in a detection/response or insider-risk role.. We are seeking mid-level and senior candidates. You have broad familiarity with operating systems and platforms such as macOS, Windows, Linux, and Kubernetes, along with experience in cloud infrastructure. Knowledge of modern adversary tactics and attack paths, data exfiltration techniques, and h

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! 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. Key Responsibilities Co-design future hardware for programmability and performance with our hardware vendors Assist hardware vendors in developing optimal kernels and add support for it in our compiler Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory h

About the Team ChatGPT is a rapidly evolving system: new capabilities ship continuously, product surfaces change quickly, and usage patterns shift week-to-week. Supporting that pace requires infrastructure that can handle real production constraints—high concurrency, unpredictable traffic patterns, complex dependency graphs, and frequent change. The ChatGPT Infrastructure team builds and operates the platforms that enable fast iteration without compromising performance or reliability. We design shared systems, data paths, rollout mechanisms, and reliability guardrails that teams rely on to ship changes to ChatGPT at scale. We focus on high-leverage infrastructure: primitives and “golden paths” that incorporate operational lessons as defaults, so engineers don’t need to rediscover failure modes, latency pitfalls, or integration issues each time they build something new. About the Role We’re hiring Senior and Staff Engineers to design and build infrastructure systems that underlie ChatGPT and multiply the effectiveness of teams building user experiences. This is not a support-only role. It’s a platform-building role: you’ll define interfaces, develop core abstractions, and create tooling to make safe, fast iteration the norm. Your work will reduce friction, prevent regressions, improve performance, and ensure systems scale gracefully as the product grows. Where You Can Have Impact You might work on one or more of the following areas (without being restricted to any single area): Platform foundations & frameworks: Core libraries, service frameworks, and shared components that standardize system building, integration, and evolution. Scalability & performance primitives: Patterns and infrastructure that reduce tail latency, improve throughput, and keep costs predictable as demand increases. Reliability guardrails: Mechanisms that prevent outages by design—rate limiting, load shedding, dependency isolation, backpressure, safe fallbacks, and robust regression contr

About the Team The Platform Systems team at OpenAI operates at the intersection of cutting-edge AI and large-scale distributed systems. We build the engineering and research infrastructure required to train OpenAI’s flagship models on some of the world’s largest, custom-built supercomputers. Our team develops core model training software and works deep in the stack - spanning collective communication, compute efficiency, parallelism strategies, fault tolerance, failure detection, and observability. The systems we build are foundational to OpenAI’s research velocity, enabling reliable, efficient training at frontier scale. We collaborate closely with researchers across the organization, continuously incorporating learnings from across OpenAI into the evolution of our training platform. About the Role As a Software Engineer, Platform Systems, you will design and build distributed systems that provide visibility into large-scale training workloads and help operate them reliably at scale. You’ll work on failure detection, tracing, and observability systems that identify slow or faulty nodes, surface performance bottlenecks, and help engineers understand and optimize massive distributed training jobs. This infrastructure is critical to operating OpenAI’s training stack and is actively evolving to support new use cases and increasingly complex workloads. This role sits at the core of our training infrastructure, blending systems engineering, performance analysis, and large-scale debugging. In This Role, You Will Design and build distributed failure detection, tracing, and profiling systems for large-scale AI training jobs Develop tooling to identify slow, faulty, or misbehaving nodes and provide actionable visibility into system behavior Improve observability, reliability, and performance across OpenAI’s training platform Debug and resolve issues in complex, high-throughput distributed systems Collaborate with systems, infrastructure, and research teams to evolve platform