Production Tech in United States

About the Team The B2B Marketing team is responsible for helping businesses understand, adopt, and get value from OpenAI’s products. B2B marketing is a major and growing priority for OpenAI as we scale our work with companies, developers, and institutions around the world. About the Role Within B2B Marketing, Demand Generation builds the integrated, full-funnel engine that connects audience insights, content, field and digital experiences, paid media, lifecycle, and sales follow-through to qualified pipeline. We partner closely with Sales, Partnerships, Product Marketing, Communications, Creative, Web, RevOps, Analytics, and regional teams to create a cohesive customer experience and scale what works. We’re looking for a Senior Webinar & Digital Events Strategist to redefine webinars and digital experiences as a high-quality demand channel. You’ll own audience strategy, portfolio design, programming principles, conversion paths, and performance recommendations while partnering closely with a Webinar Marketing Manager on production and delivery. This is a hands-on role for a strategic operator who can create compelling experiences and build the pre-event, live, and post-event systems required to turn engagement into qualified demand. In this role, you will: Owning the webinar and digital events strategy, including audience priorities, portfolio architecture, editorial themes, formats, calendar, investment decisions, and success measures. Designing experiences for specific buyer needs and journey stages, with a clear value exchange, CTA, follow-up path, and connection to broader campaigns. Partnering with Product Marketing, Content, speakers, customers, and subject-matter experts to create differentiated programs that make complex AI topics useful and concrete. Working closely with the Webinar Marketing Manager and production partners to translate strategy into clear briefs, run-of-show requirements, launch plans, QA, and delivery standards. Building integrated pr

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Secure Manufacturing & Stealth (SMS) team protects OpenAI’s most sensitive product, manufacturing, launch, and partnership work from theft, leakage, espionage, and unauthorized disclosure. We operate across physical, digital, human, and third-party domains, building practical protections that allow teams to move quickly while preserving strict need-to-know controls. About the Role We are seeking a senior Secure Manufacturing & Stealth Partner to serve as the dedicated SMS owner for Marketing. This person will build trusted relationships across Marketing, understand launches and sensitive information flows, identify secrecy risks early, and embed practical controls into planning, creative production, events, agencies, vendors, media, and executive communications. The role owns the Marketing relationship while coordinating shared SMS capabilities when investigative, prototype-handling, regional, or other specialist support is needed. In this role you will: Serve as the primary SMS Partner and trusted adviser to Marketing, building a deep understanding of its priorities, planning cycles, launches, events, external partners, and sensitive information flows. Identify secrecy and information-exposure risks early, then translate SMS requirements into practical controls that protect sensitive work without unnecessarily slowing execution. Build, document, and socialize durable operating mechanisms for compartmentalization, need-to-know access, agencies and vendors, sensitive creative production, events, demonstrations, launch preparation, codenames, watermarking, and password controls. Assess and approve Marketing systems and information workflows, identify gaps or duplication, establish secure handling requirements, and advise AI-native Marketing initiatives on permissions, data governance, and operational tracking. Coordinate

About the Team API Agents builds the shared agent harness, tools, and infrastructure that turn OpenAI’s frontier models into systems that can reliably complete real work. We carry the capabilities behind Codex into a much broader set of products and workflows across software engineering, research, finance, healthcare, enterprise operations, and more. Our work spans search and connected context, computer use, memory, delegation and multi-agent coordination, and safe execution. Sitting at the intersection of Research, Codex, infrastructure, and applied product teams, we build reusable agent capabilities that compound across the ecosystem. About the Role We are looking for an experienced backend software engineer to build the core systems behind the next generation of agents. You will design reliable services and abstractions that help agents find the right context, use tools and computers, retain knowledge, coordinate over long-running workflows, and take action safely. The role combines deep backend and infrastructure work with strong product judgment, with opportunities to work across agent runtimes, orchestration, search, execution environments, identity and permissions, observability, and evaluations. This is software and systems engineering rather than model training: success comes from strong backend fundamentals, high agency, and the ability to turn fast-moving research capabilities into dependable production primitives. In this role, you will: Design, build, and operate the shared agent harness and backend infrastructure that power long-running, high-value workflows across OpenAI and third-party products. Build reusable capabilities across search and connected context, computer use, memory, tool execution, delegation, subagents, and multi-agent orchestration. Establish the foundations agents need to operate safely in production, including secure execution environments, identity and permissions, observability, evaluations, reliability, and cost and latency effi

About Team Our Robotics team is focused on unlocking general-purpose robotics and advancing toward AGI-level intelligence in dynamic, real-world environments. Working across the full model and systems 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 physical constraints of real-world systems to improve people’s lives. About Role We are building a supply-chain organization capable of supporting our transition from laboratory-scale development to factory-scale operations. We are looking for an Inventory Manager to build and operate our inventory function from the ground up. This is a highly hands-on role. In the near term, you may start with an empty room and be responsible for determining what racks, shelving, bins, labels, scanners, workflows, and systems are needed to turn it into a functional stockroom. You will receive material, organize inventory, perform counts, move parts between buildings, resolve discrepancies, and establish the processes others will eventually follow. As we grow, you will have the opportunity to develop this foundation into a full-scale, multi-site factory inventory operation. You may hire and manage contractors or onsite inventory administrators, but this role will initially have a significant individual-contributor component and will remain accountable for day-to-day execution. This role owns inventory and internal logistics. It does not own purchasing, production planning, or inbound and outbound supplier logistics. This role is based in San Francisco, CA and requires in-person presence 5 days a week. In this role you will: Build inventory operations from the ground up across various OpenAI facilities. Design and set up stockrooms, receiving areas, and material-storage locations, including selecting racks, shelving, bins, carts, labeling equipment, scanners, and other infrastructure. Personally execute core inventory

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of this API & power-users team, you will improve the capabilities, reliability, and product fit of OpenAI’s agentic models for power users and API developers. You might design evals from real developer workflows, build training environments around production-like tool use, turn qualitative model failures into training data, evals, or post-training interventions, or drive a behavior improvement from discovery through post-training, integration, and launch. This role is intentionally broad. The strongest candidates are comfortable turning ambiguous model behavior problems into concrete progress, whether that means improving tool use, planning, instruction following, recovery from mistakes, or how models behave in API-based workflows. You should be excited to work across research, engineering, data, evals, and product to make models better at acting in real workflows. You will work closely with researchers, engineers, API/product teams, Codex, infrastructure, and safety/align

About the Team Frontier Systems Foundations, part of Compute Foundations at OpenAI, builds the systems software foundation that turns new compute infrastructure into reliable, usable capacity for frontier model training. Our mission is to make some of the world's largest GPU clusters work reliably for frontier training. We bring new platforms and clusters online, safely maintain installed fleets, and partner with hardware, infrastructure, and research teams to resolve the system-level issues that keep jobs from running. That means building and maintaining the software closest to the machine: Linux and Ubuntu operating-system images, kernels and modules, drivers, packages and repositories, disks and boot configuration, firmware integration, provisioning, and system-level validation. We make these components reproducible, compatible, and safe to operate across heterogeneous fleets. About the Role We are looking for systems software engineers with deep Linux and host-systems experience to build, qualify, and maintain the operating-system foundation for OpenAI's frontier compute fleet. Relevant backgrounds include kernel and module development, Linux distribution or image engineering, package management, firmware and driver integration, disks and boot, and bare-metal provisioning. You'll work closely with hardware engineers, vendors, and infrastructure teams to bring up new platforms, integrate system components, and debug failures across firmware, disks, boot, operating systems, kernels, drivers, and workload interactions. Your work will directly influence how quickly new capacity becomes usable and how reliably large GPU fleets operate. You should be comfortable writing and maintaining production-quality systems software and automation, but we do not expect expertise across every layer. This is an opportunity to go deep on challenging systems problems while building the image, package, qualification, and recovery paths that power the next generation of frontier models

About the Team The OpenAI 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 As a Software Engineer, Distributed Data Systems, you will design, build, and operate some of the largest distributed data systems in the world. You will be responsible for the end-to-end stack to deliver and consume top-quality data for robotics training at exabyte-scale. You’ll manage distributed data pipelines, collaborate closely with researchers to translate requirements into robust systems, and harden pipelines that serve as the backbone for OpenAI’s rapid iteration cycles. We’re looking for engineers who are detail-oriented, have strong experience with distributed systems, and excel at building reliable, large-scale systems in high-stakes environments. 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 data infrastructure such as exabyte-scale distributed data processing, data selection, automated labeling, and training data loaders. Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient. Partner with researchers to deeply understand requirements and translate them into production-ready systems. Harden, optimize, and maintain critical data infrastructure systems that power multimodal training and evaluation. Deliver the best possible data for training robotics models. You might thrive in this role if you: Have strong experience with distributed systems and large-scale infrastructure with a strong interest in data. Are detail-oriented a

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

Location: San Francisco, CA (Hybrid: 4 days onsite/week). Relocation assistance available. About the Team: We build foundational platform software that enables reliable, secure, and performant products. The team works across system layers and partners closely with adjacent engineering groups to deliver robust capabilities from concept through launch. About the Role: We’re seeking a System Software Engineer to design, implement, and debug core platform components and the pipelines that build and update system images. You’ll work across operating system layers, focusing on performance, security, and deep system debugging to ship production‑grade systems. In this role, you will: Design, implement, and debug system‑level components and services across kernel and user space. Configure and maintain OS platform services (init, services, networking, security policies) and related tooling. Build and operate image and update pipelines, ensuring reliability, reproducibility, and rollback safety. Instrument and analyze performance using profiling and tracing; optimize CPU, memory, I/O, and power usage. Own platform observability and reliability: logging, crash capture, watchdogs, and diagnostics. Collaborate with cross‑functional teams to define interfaces and deliver end‑to‑end features. Establish strong engineering practices: code review, CI, reproducible builds, and release management. Partner with external suppliers to support builds and deployments. You might thrive in this role if you: Have shipped production systems software on modern operating systems. Are proficient in C/C++ and a scripting language, and comfortable with OS internals (concurrency, memory management, filesystems, networking, power management). Bring strong systems debugging skills using debuggers, tracers, profilers, and logs across kernel/user‑space boundaries. Understand configuration of platform services and interfaces, and can translate requirements into stable, well‑documented APIs. Are fluent in u

About the Team The OpenAI 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 As a Research Engineer, Distributed Data Systems, you will design and scale the infrastructure that powers large-scale multimodal training and evaluation at OpenAI. You’ll manage distributed data pipelines, collaborate closely with researchers to translate requirements into robust systems, and harden pipelines that serve as the backbone for OpenAI's rapid iteration cycles. We’re looking for engineers who are detail-oriented, have strong experience with distributed systems, and excel at building reliable infrastructure in high-stakes environments. 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 data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security. Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient. Partner with researchers to deeply understand requirements and translate them into production-ready systems. Harden, optimize, and maintain critical data infrastructure systems that power multimodal training and evaluation. You might thrive in this role if you: Have strong experience with distributed systems and large-scale infrastructure with a strong interest in data. Are detail-oriented and bring rigor to building and maintaining reliable systems. Demonstrate excellent software enginee

About the Team With Codex we’re building an AI software engineer. One that you can pair with, delegate to, or even ask to take on future tasks proactively. Our team is a fast-moving group within OpenAI, bringing together research, engineering, design, and product. We iteratively build the Codex agent harness and product to get the most out of the model, and we iteratively train the model to be great at complex software engineering tasks. The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. We operate across research, engineering, product, and infrastructure; owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. Codex Enterprise builds the ecosystem building blocks, discovery surfaces, and enterprise capabilities that help Codex spread across developers, teams, and organizations worldwide. It is a cross-cutting team that works across the stack to build both delightful product experiences and fundamental platform capabilities. Its customers range from individual developers and small teams to large enterprises, and our mission is critical to achieving the vision of Codex as a proactive teammate. About the Role As we grow, we’re focused on turning Codex from a powerful individual tool into a production-grade teammate for entire organizations. You will work across internal OpenAI teams and external customers, from fast-moving startups to large enterprises, to make it possible to deploy, operate, and trust Codex in increasingly demanding real-world environments. As Codex’s consumer adoption accelerates, enterprise demand is growing just as quickly, and there is also increasing opportunity to expand Codex through ecosystem capabilities that unlock new workflows, integrations, and discovery. This team helps turn messy, real-world team requirements into robust, repeatable, and scalable product and

About the Team OpenAI’s Industrial Compute team is responsible for building and scaling large-scale compute capacity across first-party data centers, strategic partners, and industrial infrastructure environments. We focus on converting power, land, hardware, and operational execution into reliable compute capacity that can support frontier AI training and inference workloads. This team operates at the intersection of infrastructure delivery, hardware systems, utilities, supply chain, and capacity strategy—ensuring OpenAI can scale compute faster than traditional models allow. About the Role We are seeking a Tokens-as-a-Service (TaaS) Lead to drive the end-to-end conversion of industrial-scale infrastructure investments into usable token capacity for OpenAI workloads. In this role, you will own execution across complex compute programs where raw infrastructure capacity must be transformed into operational GPU throughput. You will coordinate across data center delivery, power, networking, hardware deployment, workload enablement, finance, and external partners to ensure capacity becomes productive tokens as quickly and efficiently as possible. This role is ideal for someone who can bridge physical infrastructure delivery with compute utilization outcomes. Success requires strong systems thinking, elite program leadership, and the ability to drive accountability across internal teams and strategic partners. In this role, you will Lead Tokens-as-a-Service programs across industrial compute environments, including first-party and partner-owned capacity. Convert delivered power, space, and hardware capacity into production-ready token throughput. Build integrated execution plans spanning construction, power energization, rack deployment, networking, cluster readiness, and workload onboarding. Partner with infrastructure engineering, hardware, networking, finance, supply chain, and operations teams. Drive external providers, EPCs, OEMs, utilities, and strategic partners t