Production Director in United States

About the Team The Cybersecurity Products team builds products at the frontier of AI and cybersecurity. Our work includes Codex Security and related cyber products that turn advances in model capability into dependable tools for defenders. We help teams find, validate, and remediate vulnerabilities, continuously improve the security of software, and test AI-powered applications before they reach production. About the Role As a Full Stack Software Engineer, you will build the product experiences and systems that make AI-powered security useful in real engineering environments. You will work across web surfaces, APIs, orchestration, data models, and integrations to help security and engineering teams move from a codebase or application to evidence-backed findings, prioritized remediation, and revalidation. You will collaborate closely with product engineers, security researchers, and customer-facing teams. The work spans fast-moving product development and hard systems problems: long-running workflows, large repositories, sensitive data, reliability, observability, and a high bar for earning user trust. 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: Build end-to-end workflows for vulnerability discovery, security scanning, red teaming, findings review, remediation, and reruns. Design and operate backend services for long-running security work, including APIs, asynchronous orchestration, durable state, and integrations with developer workflows. Make complex security results actionable through clear product surfaces, strong evidence, thoughtful prioritization, and reliable reporting. Partner with security researchers, product teams, and users to evaluate quality, reduce noise, improve coverage, and ship safely. You might thrive in this role if you: Have experience shipping production full-stack products across modern web frontends and backend s

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 We're seeking a Security Engineer to join our First-Party Hardware team. In this role, you will own the end-to-end security foundation for OpenAI's first-party AI hardware systems, working across hardware security, embedded security, system security, and practical deployment at data center scale. You will partner with silicon, hardware, firmware, infrastructure, manufacturing, operations, and security teams to define and deliver system-level device trust. This includes boot integrity, device identity, provisioning, attestation, management-plane security, storage encryption, debug controls, firmware update and recovery, RMA, and decommissioning. You will be accountable for turning threat models into requirements, requirements into implementation, and implementation into validation evidence that can support launch decisions. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you will: Own security requirements, threat models, validation strategy, and launch-readiness evidence for first-party hardware platforms from early design through production deployment. Design and review secure boot, measured boot, roots of trust, platform firmware resilience, firmware signing, recovery, and anti-rollback strategies across heterogeneous devices. Own device identity, provisioning, enrollment, attestation, certificate lifecycle, and key-management requirements across manufacturing and data center bring-up. Harden management

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role As a Supply Chain Program Manager, you will own material readiness and supply chain execution for critical hardware programs spanning custom silicon, systems, memory, storage, networking, and rack infrastructure. You will work cross-functionally with Engineering, Strategic Sourcing, Manufacturing Operations, Finance, Planning, Quality, and external suppliers to develop and execute scalable supply strategies that support aggressive product development and deployment timelines. This role requires deep understanding of hardware supply chains, material planning, NPI execution, supplier management, and operational scaling in constrained and rapidly evolving environments. In this role you will: Material Readiness & Supply Planning - Own end-to-end material readiness across NPI and production phases, including building the necessary framework and processes for enablement. Drive supply planning and execution for long lead-time and constrained commodities including ASICs, HBM, DDR, SSDs, networking, optics, power, thermal, and mechanicals. Build and manage material readiness plans aligned to proto/pre-EVT, EVT, DVT, PVT, and mass production schedules. Monitor supply health, lead times, inventory positions, allocation risk, and capacity constraints. Drive shortage management, allocation mitigation, and recovery planning. Coordinate supply commits, forecast alignment, and supply continuity planning with suppliers and manufacturing partners. Cross-Functional Program Ma

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect our model weights, customer data, and critical systems across multiple cloud environments. We partner with teams across OpenAI—Applied Engineering, Research, IT, and Security—to provide a secure and scalable platform for permissioning, orchestration, and innovative AI research. About the Role We’re looking for a Staff+ Software Engineer to help build and evolve the identity infrastructure that supports OpenAI’s research, engineering, and internal platforms. This role sits at the intersection of cloud infrastructure, identity systems, and software engineering. You’ll work across production systems, infrastructure-as-code, cloud control planes, identity providers, and operational infrastructure to build secure, scalable, and reliable systems used broadly across the company. The ideal candidate has experience building and operating large-scale, mission-critical systems with strong reliability and security requirements, and is comfortable writing production code, designing distributed systems, and driving ambiguous projects from 0 to 1 while building the operational rigor needed to run critical infrastructure over time. In this role, you will: Lead the architecture, development, and operation of identity infrastructure that spans cloud platforms, internal systems, and critical engineering services. Design and evolve systems for authentication, authorization, access governance, auditability, and policy enforcement with a strong focus on reliability, scalability, and secure-by-default design. Build foundational infrastructure and platform capabilities that are broadly used across engineering, research, and security teams. Improve the reliability, observability, performance, and op

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 We're seeking a System Software Engineer to join our First-Party Hardware team. In this role, you will design, build, integrate, and validate low-level system software for the manageability and health of OpenAI's first-party AI hardware systems. You will work across BMC, Linux, firmware interfaces, automation infra, boot and recovery, hardware diagnostics, telemetry, host and platform drivers, network software interfaces, and manufacturing and fleet readiness. A major part of this role is owning the acceptance path for partner-delivered system software: defining requirements, reviewing code and artifacts, reproducing builds, building tests, pushing fixes, and producing the evidence needed for launch decisions. This role is hands-on and high-ownership. You will write and review low-level software, debug issues across hardware and software boundaries, build infra and automation to test and manage devices in lab, guide partner deliverables, build validation evidence, and help carry platforms from bring-up through production deployment. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you will: Design, develop, and maintain low-level firmware and system software for first-party AI hardware manageability, including BMC software, Redfish services, gNMI telemetry, firmware update and recovery flows, BIOS/UEFI interactions, platform drivers, and hardware diagnostics. Own integration and acceptance of partner and ve

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu

About the Team Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment. In this role, you will: Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production. Work alongside researchers to enable advanced research through awesome engineering. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues. Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware. You might thrive in this role if you: Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference. Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. Have at least 5 years of professional software engineering experience. Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc. Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems. Have need

About the Team We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance. This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack. About the Role We’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident. A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT). You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack. This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most p

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 We are seeking a Technical Lead to lead deployment and operations for OpenAI’s Silicon & Systems team. This person will become the Directly-Responsible Individual responsible for bringing OpenAI’s custom silicon and associated systems into data center environments, ensuring successful deployment, bring-up, validation, operational readiness, and ongoing reliability at scale. This role sits at the intersection of silicon, systems, infrastructure, data center operations, and software. You will lead a team focused on taking new hardware platforms from lab validation into production data center deployment. You will be responsible for building the operational processes, technical workflows, tooling, and cross-functional alignment required to deploy and operate custom AI hardware reliably in OpenAI’s supercomputing infrastructure. The ideal candidate is both a strong leader and a deeply technical operator. You should be comfortable staying close to the technical details of hardware bring-up, fleet deployment, debugging, system validation, data center integration, and production operations. This role requires strong execution, excellent cross-functional judgment, and the ability to drive clarity in ambiguous, fast-moving environments. In this role, you will: Lead a team responsible for deployment and operations of OpenAI’s custom silicon and systems in data center environments Own the path from hardware bring-up and validation through production deployment, operati

About the Team The Hardware Health and Observability team owns the end-to-end health lifecycle of OpenAI’s global compute fleet. Our mission is to maximize healthy, usable compute across accelerator vendors, generations, cloud providers, and regions through reliable health signals, automated remediation, and scalable operational tooling. We build the systems that observe, detect, remediate, and verify hardware issues across GPUs, CPUs, networking, and platform infrastructure, enabling frontier model training and inference workloads to run reliably at hyperscale. We are the last line of defense for the success of OAI’s production and research workloads. About the Role On the Hardware Health and Observability team, you’ll build critical infrastructure that keeps OpenAI’s largest compute clusters healthy and operational at scale. Even small numbers of unhealthy systems can impact large-scale training and inference workloads. This team focuses on minimizing downtime, improving fleet efficiency, and ensuring compute resources remain continuously available to researchers and product teams. Engineers on this team own problems end-to-end, from defining health signals and debugging failures to building automated remediation systems that operate across millions of GPUs globally. In this role, you will: Define and maintain health signals across GPUs, CPUs, networking, and platform infrastructure. Build and evolve health checks that detect, remediate, and verify failures at scale. Ensure critical health checks execute with minimal latency to maximize workload uptime. Investigate hardware failures and system-level issues across large-scale compute environments. Own node lifecycle workflows including drain, quarantine, repair, RMA, and return-to-service processes. Build automation and tooling that enables global cluster management with minimal manual intervention. Partner with workload, reliability, and provider teams to integrate health signals into training and inference system

About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Strategic Sourcing & Procurement function plays a critical role in enabling OpenAI to deliver impact across research, product development, technology infrastructure, and services by helping the company scale responsibly, securely, and with strong commercial discipline. Our work sits at the intersection of innovation and execution. We partner closely with teams across OpenAI to translate rapidly evolving business needs into scalable, compliant, and economically sound external partnerships. As OpenAI continues to grow at pace, services sourcing is becoming increasingly strategic across the company. Every business unit relies on external service providers in different ways — to extend capacity, access specialized expertise, support operations, and accelerate execution. Done well, Procurement becomes a source of trust and momentum, helping OpenAI move faster with the right partners, stronger commercial outcomes, and the right level of protection. About the Role We are seeking an experienced Strategic Sourcing (GTM) Leader to lead strategic sourcing and commercial enablement for OpenAI’s Go-to-Market organization across B2B and B2C channels. You will manage substantial and rapidly growing spend while shaping sourcing strategies and scalable commercial pathways across Media, Creative, Production, Influencer, Agency, Sponsorships, Analytics, Communications, and Event suppliers in support of high-impact global initiatives. You’ll help evolve our GTM procurement function from reactive deal support into a speed-enabling, scalable commercial engine that delivers cost efficiency, launch readiness, and strong governance in a fast-moving environment. In this role, you will: Develop and execute sourcing strategies across GTM, Brand, Global Affairs, Events, Growth, and Partnership activities—spanning both B2B and B2C channels—that align with our mission and b

AI Systems Engineer - Codex Core Agents About The Team The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex. About The Role We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements. What You’ll Do Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely. Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments. Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures. Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to

About the Team 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 seeking a Senior Mechanical Engineer to lead the design, integration, and sustaining engineering of mechanical subsystems in robotic platforms. You will work closely with experienced engineers and cross-functional partners to set functional requirements, develop and iterate on hardware to meet program expectations. This role is aimed at candidates with strong fundamentals in mechanical system design — including tolerance, alignment, load paths, wear, and failure modes — and robotics. You will contribute to real hardware programs moving from prototype through early production. You will lead both new subsystem development and ongoing improvements to existing systems based on testing, field performance, and manufacturing feedback. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Lead the design and iteration of mechanical subsystems, including structures, mechanisms, and actuators. Create and maintain CAD models, assemblies, and drawings with appropriate tolerancing and documentation. Build and test prototypes, supporting debugging of mechanical issues such as fit, alignment, friction, and wear. Assist in developing test methods and executing validation to evaluate performance, durability, and failure modes. Work with cross-functional teams to integrate mechanical components with sensors, actuators, and control systems. Support transition of designs from prototype to manufacturable assemblies, incorporating DFM and DFA considerations. Collaborate with manufacturing partners

About the Team: GTM Innovation is a product engineering team with a charter to automate 100% of digital knowledge work in OpenAI's GTM, so sellers spend more time directly with customers. AGI-level reasoning doesn’t mean organization-level transformation “just works” out of the box; orgs must be redesigned around abundant intelligence and persistent virtual coworkers. Our team builds and scales a fleet of virtual coworkers that operate as full-time members of the account team, and redefines how our human-first revenue organization interacts with their agentic teammates. About the Role We’re looking for backend software engineers with a product mindset to join the GTM Innovation team. You’ll help OpenAI meet the world at scale. You’ll partner closely with go-to-market teams to understand their workflows, identify leverage points, and ship novel solutions using OpenAI’s API platform. You’ll move quickly from prototype to production, and your work will directly shape how customers experience our technology in the field. This role is ideal for engineers who want to be close to users, own end-to-end outcomes, and help define entirely new categories of enterprise software. In this role, you will: Build high-impact applications and tools that accelerate OpenAI’s go-to-market efforts Work across the full product lifecycle for GTM: prototype, iterate, ship, and maintain Embed with Sales, Technical Success, and Revenue Operations to identify user needs and build for them Apply OpenAI’s models in novel ways to solve real-world customer and internal workflow problems Translate learnings into feedback for Applied and Research teams to inform product development You’ll thrive in this role if you: Have 4+ years of experience as a software/ML/product engineer working on user-facing systems Former founder, or early engineer at a startup who built a product from scratch is a plus Are fluent in Python or JavaScript and comfortable building full-stack applications Have built or prototy

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 On the Accelerators team, you will help OpenAI evaluate and bring up new compute platforms that can support large-scale AI training and inference. Your work will range from prototyping system software on new accelerators to enabling performance optimizations across our AI workloads. You’ll work across the stack, collaborating with both hardware and software aspects - working on kernels, sharding strategies, scaling across distributed systems, and performance modeling. You'll help adapt OpenAI's software stack to non-traditional hardware and drive efficiency improvements in core AI workloads. This is not a compiler-focused role, rather bridging ML algorithms with system performance - especially at scale. In this role, you will: Prototype and enable OpenAI's AI software stack on new, exploratory accelerator platforms. Optimize large-scale model performance (LLMs, recommender systems, distributed AI workloads) for diverse hardware environments. Develop kernels, sharding mechanisms, and system scaling strategies tailored to emerging accelerators. Collaborate on optimizations at the model code level (e.g. PyTorch) and below to enhance performance on non-traditional hardware. Perform system-level performance modeling, debug bottlenecks, and drive end-to-end optimization. Work with hardware teams and vendors to evaluate alternatives to existing platforms and adapt the software stack to their architectures. Contribute to runtime improvements, compute/communication over