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About the Role The Mechanical Commissioning Project Engineer owns mechanical commissioning planning, readiness, quality coordination, and test execution oversight for the project. This role ensures mechanical systems are installed, inspected, started, balanced, controlled, and tested in a way that supports reliable integrated facility performance. Reports to the Commissioning Project Lead and partners closely with mechanical contractors, equipment vendors, design/engineering teams, the electrical commissioning lead, controls stakeholders, and vendor field/test engineers. Key Responsibilities Develop and maintain the mechanical commissioning scope, readiness criteria, inspection strategy, and discipline test execution plan. Review mechanical design packages, specifications, submittals, method statements, controls narratives, sequence assumptions, and testing requirements for commissionability and risk. Coordinate mechanical QA/QC inspections with contractors and vendor field/test engineers, including installation checks, pre-functional readiness, deficiency capture, and closeout tracking. Own mechanical commissioning procedure development and review, including equipment startup, functional testing, controls verification, balancing prerequisites, failure mode validation, and integrated systems testing inputs. Coordinate with equipment vendors on factory/site acceptance requirements, startup support, test prerequisites, documentation packages, and vendor participation during critical tests. Support readiness and execution for cooling, ventilation, hydronic, pumping, heat rejection, controls, and other project-specific mechanical systems. Lead discipline-level review of mechanical test results, deficiencies, corrective actions, retest requirements, trend logs, and acceptance evidence. Maintain mechanical commissioning dashboards and status inputs for the Commissioning Project Lead, including risk items, resource needs, test readiness, and issue aging. Partner with the E

About the Team The Monetization Data Systems team builds the trusted data and product systems that power how the company develops, measures, and improves monetization products. We bring together product usage, pricing, billing, ads, payments, and financial data to help Product, Engineering, Finance, and GTM teams make better decisions and deliver reliable customer experiences. We work at the intersection of data engineering, product engineering, platform engineering, Finance, and GTM. Our goal is to turn complex monetization and financial data into accurate, explainable, and timely data products while building systems that scale with the growth and complexity of the business. About the Role We are looking for a Senior Software Engineer to design and build the next generation of our monetization data platform. You will own high-impact platform systems end to end, from architecture and implementation through testing, deployment, observability, and ongoing operation. This is a hands-on role for an engineer who enjoys solving ambiguous customer and business problems, designing durable systems, and partnering closely with Product, Data, Finance, Accounting, and GTM. You will help define technical direction, raise the engineering bar, and turn monetization opportunities into reliable, scalable product experiences and platform capabilities. In this role, you will: Design, improve, and operate reliable, scalable backend services that power pricing, billing, ads, payments, entitlements, and other monetization platform capabilities. Own the architecture and implementation of critical workflows relevant to monetization data, data contracts, and integrations across product and business systems. Establish strong guarantees for correctness, availability, security, performance, reconciliation, and auditability across business-critical systems. Build reusable platform capabilities and developer tools that enable product teams to launch, measure, and iterate on monetization products

About the Team OpenAI’s Application Engineering team builds the internal products and platforms that help OpenAI operate securely and at scale. We engineer, own, and evolve OpenAI’s core productivity ecosystem, creating secure applications, integrations, automation, and reusable tooling where off-the-shelf software is not enough. Our work spans employee-facing experiences and the services, APIs, control planes, and governance that make them reliable, permission-aware, and scalable. We also act as a customer zero for OpenAI’s technology, building the enterprise foundations that let employees and agents safely access the context, tools, and actions they need. We partner closely with IT, Security, product teams, and platform providers to turn company-wide problems into durable systems, learn from real internal workflows, and help shape the products we deploy. We create paved paths that let teams move quickly without compromising security or operational quality. About the Role As a Staff Software Engineer on Agent Productivity, you will shape the foundation that enables teams to build agents with secure access to the context and capabilities they need. Slack will be the first and deepest implementation surface—and where you spend most of your time—owning its application architecture, integrations, APIs, governance, and administration automation while building patterns that extend to internal systems, identity platforms, and other enterprise applications. This is a hands-on engineering role with broad organizational impact as agents support more employee workflows. You will define platform architecture, build reusable foundations, and establish secure patterns for identity, permissions, connectivity, and operations that make agents easier to develop, deploy, and manage. In this role, you will: Own the technical strategy and architecture that enable teams to build, connect, and deploy agents quickly and safely, using Slack as the primary implementation surface. Design and

About the Team OpenAI’s Industrial Compute organization is building the infrastructure required to support the next generation of frontier AI systems. Through a combination of strategic partnerships and self-built data center campuses, we are scaling the physical infrastructure needed to deliver compute at unprecedented scale. The Commissioning organization is responsible for ensuring this infrastructure is safely tested, validated, integrated, and transitioned into reliable operations. As the portfolio grows, the team is building common standards, processes, tools, and reporting systems that allow commissioning programs to operate consistently across projects while giving teams and leadership clear visibility into readiness, risk, and execution. About the Role We are seeking a Commissioning Program Manager to build and scale the operating systems behind OpenAI’s infrastructure commissioning programs. You will own the development and continuous improvement of commissioning standards, processes, tools, dashboards, and KPIs across the infrastructure portfolio. You will work closely with commissioning and construction teams to translate field execution needs into practical playbooks, workflows, templates, metrics, and reporting mechanisms that teams can use from construction readiness through testing and turnover. This role sits at the intersection of infrastructure delivery, program management, process design, and data. The ideal candidate understands how complex construction projects operate and can turn fragmented workflows and project data into repeatable systems that improve execution without creating unnecessary administrative burden. Key Responsibilities Develop and maintain commissioning program standards, playbooks, process maps, templates, checklists, stage gates, and acceptance criteria across infrastructure projects. Establish consistent workflows for commissioning planning, construction readiness, QA/QC, issue management, document control, testing evidence

About the Team We're building the foundation for a new kind of AI coworker: persistent agents that have their own environments, can meet people wherever they work, and continue making progress for as long as a task requires. Our goal is to help individuals, teams, and organizations delegate meaningful work to AI—not just ask questions or complete a single turn. Our work brings together product, agent, and infrastructure capabilities across OpenAI. Together, we are creating always-on virtual coworkers that can carry context across tasks, operate through the right tools and channels, and deliver reliable results in real workplace environments. About the Role We’re looking for a full stack product engineer to shape how people discover, direct, and collaborate with AI coworkers. You’ll own product experiences end to end, spending roughly equal time building intuitive frontend surfaces and the backend systems that make agentic workflows persistent, reliable, and useful. You’ll work at the intersection of product engineering, design, agent capabilities, and enterprise readiness—turning rapidly evolving model and platform capabilities into experiences customers can understand, trust, and use every day. In this role, you will: Design, build, and ship full stack product experiences that help people and teams delegate meaningful work to persistent AI coworkers. Create intuitive frontend interfaces for directing agents, reviewing their progress, understanding their actions, and collaborating on the work they produce. Build backend APIs, services, and data models that support persistent agent state, asynchronous execution, orchestration, and progress reporting. Develop workflows that help agents access relevant context, use tools, and collaborate with people across workplace surfaces and channels. Partner with product, design, research, and engineering teams to turn shared capabilities into cohesive products. Build trust into the product through clear user controls, understanda

About the Team API Multimodal builds the developer-facing products and infrastructure that bring OpenAI’s image, audio, and real-time model capabilities into the world. We are responsible for high-scale APIs for image generation, speech transcription, speech generation, and low-latency voice interactions. We partner closely with Research and Inference to bring frontier model capabilities to developers and use customer feedback to improve our models. About the Role As a software engineer on API Multimodal, you will build and operate the products and distributed systems behind OpenAI’s image, audio, and real-time APIs. You will work across model integration, API design, and production infrastructure to turn new research capabilities into reliable developer experiences. This hands-on role combines backend and systems depth with product judgment: you will own projects end to end, partner with Research, Inference, and Safety, and help make multimodal AI useful at scale. Model training experience is not required. In this role, you will: Design, build, and ship developer-facing APIs and backend services that serve frontier models. Architect low-latency streaming, request, session, and model integration systems that make complex multimodal interactions reliable and intuitive at scale. Work directly with Research to bring new model capabilities into production, shape the systems around them, and incorporate feedback from real-world developers and customers. Own the availability, latency, scalability, and cost efficiency of the services you build. Own projects from technical design and implementation through launch and ongoing iteration, while raising the team’s engineering standards. Your background might look something like: 7+ years of professional experience, excluding internships, in backend, infrastructure, platform, or product engineering roles. A track record of designing, building, and operating production backend services, developer-facing APIs, or distributed syste

About the Team The Core Models team helps shape how OpenAI’s frontier models are built, measured, and launched. We work across Research, Engineering, Model Design, Data Science, and Product to turn advances in model capabilities into reliable, useful experiences for people. Our scope includes model planning and launches as well as building data flywheels, evaluations and measurement systems to ensure our models have strong capabilities and behavior. About the Role As a Product Manager for the Core Models team, you'll be at the forefront of defining and guiding the future of how our AI models work in real-world applications. You will connect user needs to model and systems decisions: how prompts are understood; how information is aggregated and made useful for training and evaluation data; and how capabilities move from research prototypes into the mainline model and launch stack. You will operate comfortably across research, infrastructure, and consumer product surfaces, creating clarity where ownership and technical boundaries are still emerging. 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: Translate user and product goals into clear model requirements, system architecture choices, and research priorities across query understanding, indexing, retrieval, ranking, tool boundaries, data, training, inference, and evaluation. Build closed learning loops that turn product usage, explicit feedback, and other user signals into datasets, evaluations, experiments, training priorities, and launch decisions. Define success across offline evaluations and online product metrics, balancing model quality, usefulness, latency, safety, reliability, and cost. Partner closely with post-training research, applied product engineering, Model Design, and Data Science to integrate capabilities into the mainline model stack. Create reusable platforms and operatin

About the Team OpenAI’s Industrial Compute organization is building the infrastructure required to support the next generation of frontier AI systems. Through a combination of strategic partnerships and self-built data center campuses, we are scaling the power, cooling, electrical, mechanical, and controls infrastructure needed to deliver compute at unprecedented scale. The Commissioning organization is responsible for ensuring this infrastructure is safely tested, validated, integrated, and transitioned into reliable operations. For our self-build campuses, the team operates through a hybrid delivery model: OpenAI provides commissioning leadership, discipline ownership, governance, and project integration, while commissioning partners provide field and test engineering capacity to support inspections, startup, testing, and turnover. About the Role We are seeking a Commissioning Project Lead to own the commissioning strategy and execution for a large-scale, self-build data center project. You will lead the overall commissioning program from early construction planning through startup, functional testing, integrated systems testing, and final turnover. You will establish the commissioning execution plan, integrate commissioning activities into the master project schedule, coordinate multidisciplinary readiness, and lead the vendor commissioning partners providing field and test engineering capacity. This role serves as the primary commissioning interface to project leadership, construction management, contractors, equipment vendors, operations, and commissioning partners. You will be responsible for creating clarity across organizations, identifying readiness and schedule risks early, and ensuring the facility progresses through testing and turnover against clearly defined acceptance criteria. The role will initially support planning and coordination in a hybrid capacity and transition to full-time onsite presence as construction, inspections, startup, testing, and t

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 Industrial Compute organization is building the world's most advanced AI infrastructure ecosystem. Working alongside our cloud partners, infrastructure providers, and internal engineering teams, we operate hyperscale AI campuses that support the training and deployment of frontier AI models. The Site Operations team serves as OpenAI's on-site operational presence, helping ensure campuses operate safely, efficiently, and in alignment with Industrial Compute standards. We work closely with Hardware Operations, Infrastructure Delivery, Network Operations, Security, Facilities, Construction, and our infrastructure partners to support day-to-day site execution and maintain operational readiness. As Industrial Compute continues to expand globally, Site Operations plays a critical role in ensuring each campus is prepared to support reliable AI infrastructure at scale. About the Role We are seeking a Site Operations Technician to support the daily operation of Industrial Compute campuses. This role acts as OpenAI's on-site technical representative, helping coordinate activities across hardware operations, facilities, construction, logistics, security, and external service providers. You will perform routine site inspections, support asset tracking, coordinate vendor activities, assist with operational readiness, document site conditions, and help ensure infrastructure issues are identified and resolved quickly. The ideal candidate enjoys working in highly technical environments, is detail-oriented, and thrives in fast-paced operational settings where no two days are the same. Key Responsibilities Perform routine walkthroughs of Industrial Compute facilities to verify operational readiness and identify potential issues. Monitor site conditions and report abnormalities involving hardware spaces, network rooms, utilities, logistics areas, and common infrastructure. Support coordination of vendors, contractors, and partner organizations performing work o

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

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 Infrastructure Engineering function sits within IT and is responsible for reliably building, deploying, and operating critical on prem and hybrid environments that power internal services and critical R&D environments. This is an early, high-leverage technical role focused on applying strong Site Reliability Engineering discipline to environments where uptime, safety, recoverability, and security are non-negotiable. This person helps replace bespoke, one-off infrastructure with standardized infrastructure-as-code building blocks that compound reliability and operational leverage as OpenAI scales. About the Role We are looking for an experienced Site Reliability Engineer working on security infrastructure to design, build, and operate reliable, secure, and scalable infrastructure that underpins identity, access, endpoint, and shared platform services across the company. In this role, you will be a senior technical owner for infrastructure and identity systems end to end, from architecture and implementation through policy enforcement, upgrades, recovery, and day-two operations. You will build durable, production-grade platforms that remove operational friction, enforce security by default, and enable teams to move faster with confidence. This role is well suited for a hands-on senior engineer who thrives in ambiguity, enjoys owning complex systems end to end, and raises the reliability and security bar by replacing fragile implementations with standardized, repeatable infrastructure. This role is based in our San Francisco HQ and requires in-office presence. In this role, you will: Design, build, and operate reliable infrastructure across on-prem, hybrid, shared, and product adjacent environments. Establish standardized infrastructure patterns that replace bespoke implementations with repeatable, auditable, secure-by-default systems. Own the lifecycle of critical infrastructure platforms, including provisioning, deployment, upgrades, patching,

About the Team The Applied team brings OpenAI’s technology to the world through products used by hundreds of millions of people and by developers and businesses building on our APIs. We work across research, engineering, product, policy, safety, and operations to deploy frontier AI systems responsibly and safely. The Trust & Safety Data Engineering team builds the data foundations that help OpenAI understand, detect, investigate, and mitigate abuse and safety risks across our products. We partner with Integrity, Investigations, Safety Systems, Product Policy, Privacy, Data Science, Engineering, and Data Platform to create reliable, privacy-safe datasets and pipelines for fraud and abuse detection, enforcement workflows, safety measurement, ML feature generation, launch readiness, and transparency reporting. About the Role We are hiring a Technical Lead Manager to lead and grow the Trust & Safety Data Engineering team. This is a hands-on leadership role for someone who can set strategy, shape data architecture, align senior stakeholders, coach engineers, and drive execution on high-impact data systems. You will help turn fragmented launch and incident support into durable, reusable, privacy-safe data foundations that Trust & Safety teams can rely on. The systems your team builds will help OpenAI detect risk, investigate abuse, power operational workflows, develop and evaluate safety models, measure interventions, support product launches, and report accurately on platform integrity. In This Role, You Will Lead and grow a high-performing Trust & Safety Data Engineering team. Define the roadmap and technical strategy for Trust & Safety data systems. Build canonical, privacy-safe datasets and pipelines for abuse detection, fraud detection, risk signals, enforcement, scaled review, transparency reporting, and safety monitoring. Create reusable foundations for Trust & Safety model development, including features, labels, training data, backtesting,