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About the Team OpenAI’s Governance, Risk, and Compliance team helps ensure security and privacy are grounded in how our products and systems actually operate. Assurance Operations partners with Security, Engineering, Infrastructure, Product, Privacy, and Legal to make controls provable, risk decisions explicit, and audit readiness a result of well-designed systems. About the Role We are hiring a technical, product-minded GRC builder who can own consequential audits while improving the control and evidence systems behind them. You will build a reusable common control framework, use Codex to automate assurance work, validate changing system scope, and turn repeated audit friction into measurable improvements. We are looking for someone who questions inherited assumptions, solves novel problems creatively, works closely with engineers, and makes the next audit easier by improving the underlying system. You’ll be responsible for: Lead external, internal, customer, and certification audit work from scoping through evidence review, fieldwork, remediation, and closeout. Build a common control framework linking risk, control intent, implementation, owner, system, environment, evidence, and applicable frameworks. Validate actual scope and ownership instead of assuming last year's controls, product boundaries, or evidence remain accurate. Use Codex to build and test evidence checks, control mappings, request triage, owner workflows, monitoring, and remediation reporting. Partner with engineers on cloud architecture, identity, logging, data flows, software changes, vulnerabilities, and control effectiveness. Design maintainable, permission-aware tools that preserve source provenance, human review, and evidence integrity. Reduce repeated requests and operational burden for control owners through measurable workflow improvements. Define roadmaps, decision rights, milestones, success metrics, and clear cross-functional escalations. We’re looking for someone with: Direct ownership

About the Team OpenAI's Professional Services team helps organizations move from AI ambition to durable production outcomes. We partner with customers on complex deployments and build the strategy, commercial models, operating mechanisms, and delivery capacity needed to realize value from OpenAI's models and products. The team works across Go-to-Market, Forward Deployed Engineering, Technical Success, Finance, Product, Legal, Data, Systems, and delivery partners. We are building a services motion that is customer-centered, commercially rigorous, operationally scalable, and deliberately connected to product adoption. About the Role We are seeking a senior GTM Strategy & Operations professional to build and scale the operating system for OpenAI's Professional Services business. This is a foundational, hands-on individual contributor role at the intersection of business strategy, finance, go-to-market, and delivery. You will turn ambiguous questions—what we offer, how we price and package it, how we plan capacity, and how we measure performance—into clear decisions and repeatable mechanisms. You will own business planning, pricing and packaging, forecasting and modeling, management reporting, and cross-functional strategic initiatives. You will build integrated views of demand, staffing, revenue, margin, and delivery performance; replace one-off analyses with durable processes; and create operating cadences that help leaders act early. You will be a trusted partner to Professional Services, GTM, FDE, Technical Success, Finance, Product, Legal, Revenue Operations, and Data leaders. The right person combines direct Professional Services judgment with rigorous analytics, executive communication, and the willingness to build the model, process, or dashboard themselves. You’ll be responsible for: Define and drive the business and GTM strategy for Professional Services, including target customer needs, offer portfolio, positioning, pricing and packaging, partner motions,

About the Team OpenAI's research training infrastructure powers how our frontier models are trained and evaluated. The Simulation team sits at the intersection between the agentic harness that powers OpenAI's products and the research infrastructure where GPT-next is trained, ensuring that our model's training environment is as realistic as possible. This team owns the integration layer that connects our production harness capabilities into the training stack. The work is highly cross-functional and high leverage: researchers depend on it to run experiments and evaluations reliably as well as to develop the next generation of harness capabilities. Failures in this surface can materially affect training velocity and correctness. About the Role We're looking for a Principal Software Engineer to lead the architecture and evolution of the Simulation Platform. You'll own a critical interface between research and engineering, building the systems, APIs, and operational patterns that let researchers use agentic coding infrastructure safely and effectively in training environments. This role is ideal for a senior backend or infrastructure engineer with strong technical judgment, product sense for highly technical users, and the ability to drive execution across multiple teams. The highest-leverage work is building robust infrastructure that supports and accelerates research without compromising engineering quality. In this role, you will Design, build, and evolve the integration between the Codex harness that powers OpenAI's products and research training infrastructure used for training GPT-next Build a platform for our LLMs to train and be evaluated in simulated environments that mimic their deployment setting as closely as possible, on every axis: agentic harness, compute substrate, timing, tools, data sources, humans in the loop, and more Own major integration surfaces end-to-end, from architecture and API design through rollout, operations, and long-term maintenance Bu

About the Team OpenAI’s Infrastructure Operations team is responsible for the availability, reliability, and operational excellence of one of the world’s largest AI infrastructure networks. The team owns day-to-day operations of production AI networks across Industrial Compute's data centers, working with colocation providers, deployment teams, and hardware vendors to deliver highly available GPU infrastructure for AI training and inference workloads. About the Role We are seeking an Infrastructure Operations Engineer to operate and improve the large-scale Ethernet fabrics that support GPU clusters, storage systems, and management infrastructure. This role combines hands-on production operations with automation, observability, and incident response across a global AI network. The ideal candidate has experience operating high-availability data center, cloud, AI, or HPC networks and can move comfortably from physical-layer troubleshooting to routing and fabric behavior, change execution, and root-cause analysis. You will partner closely with network architecture, systems engineering, GPU engineering, storage engineering, security, deployment, site operations, service providers, colocation partners, and hardware vendors to raise reliability and reduce operational toil. Key Responsibilities Own the operational health, availability, and reliability of production AI network infrastructure across Industrial Compute's data centers. Monitor, troubleshoot, and resolve network incidents while meeting service-level objectives (SLOs), reducing Mean Time to Detect (MTTD), and minimizing Mean Time to Recovery (MTTR). Operate and maintain large-scale Ethernet fabrics supporting GPU compute, storage, and management networks. Execute production network changes, maintenance windows, and capacity expansions with minimal customer impact. Manage the hardware lifecycle, including switch and optics replacements, RMA coordination, software upgrades, and preventive maintenance. Support new A

About the Team OpenAI's Marketing team helps customers understand, adopt, and get value from OpenAI's products and platform. The SMB Ads Marketing team is building the growth engine for small and medium-sized business advertisers: helping them discover the platform, sign up, launch campaigns, understand performance, and grow spend over time. We take a data-driven approach to understanding customer needs, market dynamics, and funnel behavior. We partner closely with Product, Engineering, Data Science, Sales, Partnerships, Marketing Operations, Design, and Communications to create a cohesive end-to-end advertiser experience and help businesses unlock value from OpenAI's advertising platform. About the Role We are hiring a Growth Marketing Manager, SMB Ads to help build and execute high-velocity growth programs for small business advertisers. This person will work across acquisition, activation, lifecycle, and conversion, with an initial focus on helping advertisers move from interest and sign-up to first meaningful spend & retention over time This is a hands-on growth role for someone who loves turning ideas into shipped experiments. You will build campaigns, lifecycle journeys, landing page tests, messaging tests, audience experiments, AI-assisted workflows, reporting improvements, and practical conversion programs. As the SMB Ads business grows, this role may continue to support acquisition and activation and expand deeper into same-store growth, lifecycle, retention, and repeat spend. In This Role, You Will: Execute growth experiments across acquisition, activation, lifecycle, and early retention. Build email, in-product, landing page, audience, messaging, and offer tests that help SMB advertisers reach first spend and repeat value. Use AI tools to prototype marketing assets, automate workflows, analyze funnel data, generate creative variations, and build internal growth systems. Partner with Growth, Product, Engineering, Data Science, and Marketing Operations

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a

About the Team The Applied AI team safely brings OpenAI's technology to the world. We released ChatGPT, Plugins, DALL·E, and the APIs for GPT-4, GPT-3, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. We serve end-users directly through ChatGPT, and serve developers through our APIs, which power product features that were never before possible. About the Role The Engineering Acceleration team designs, builds and maintains the foundational systems that engineers use to build ChatGPT and the API. This is a fast-growing team and you will get a chance to own and define the strategy, vision, and plan for how to increase developer productivity. In this role, you will: Drive the design, development, and implementation of tools, systems, and processes that accelerate engineering velocity, reduce manual effort, and increase the quality of output. Use our latest AI tools to re-think how we can be the most productive team in the industry. Work closely with various teams within OpenAI to understand their workflows, challenges, and needs, and ensure the tools and systems built by the Engineering Acceleration team address these requirements. Bring new features and research capabilities to the world by partnering with product engineers to lay the necessary technical foundations. Guide and advise product engineering teams on best practices for ensuring observable, scalable systems. Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years of experience in engineering, including 3+ years of experience in infrastructure building tooling for developers. Have experi

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the Role Our GTM team is uniquely positioned to help customers realize the transformative potential of advanced AI models for their businesses and end users. As an individual contributor on the GTM Operations team, you’ll play a critical role in designing and scaling the operational systems that power our sales organization. This role will serve as a trusted partner to GTM leadership, building the end-to-end ops design for sales lifecycle from lead routing through territory design, opportunity management, deal execution, and delivery readiness. This role combines systems and process design with operational performance management, delivering insights and driving automation to improve field efficiency and velocity. You’ll collaborate cross-functionally with Marketing Ops, Enterprise Systems, Product, Delivery, Finance, Enablement, Legal, Deal Desk, and Security to develop scalable infrastructure, streamline workflows, and enable scalable growth across the business. In this role, you will: GTM Data,Governance & Routing: Create a reliable GTM data foundation that makes SFDC easier to use and ensures leads, accounts, and opportunities are accurately routed, defined, enriched, and actionable. Design and manage lead and campaign routing; define requirements and partner with systems and marketing ops on build. Implement alerting, monitoring, an

About the team The Applied team safely brings OpenAI's technology to the world. We released ChatGPT; Plugins; DALL·E; and the APIs for GPT-5, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon. Our customers build fast-growing businesses around our APIs, which power product features that were never before possible. ChatGPT is a prime example of what is currently possible. We simultaneously ensure that our powerful tools are used responsibly. Safe deployment is more important to us than unfettered growth. The Fraud Engineering team works within our Applied Engineering organization identifying and responding to fraudsters on our platform. We are looking for a software engineer with anti fraud & abuse experience to help architect and build our next-generation anti-fraud systems. About the role The Scaled Abuse team protects OpenAI’s products and customers by detecting, preventing, and responding to fraudulent and abusive behavior at scale. We build and operate the backend and data systems that power real-time detection, investigation workflows, and enforcement — balancing strong protections with a great user experience as the platform grows. Our work sits at the intersection of engineering and abuse expertise: we partner closely with Trust & Safety, Security, and Product to understand emerging attack patterns, translate messy signals into clear system behavior, and continuously harden our defenses. The problems are dynamic and ambiguous by default, so we value engineers who can quickly dive into an unfamiliar codebase, develop strong intuition about how it works end-to-end, and propose pragmatic improvements that make the entire stack more resilient. In this role, you will: Design and build systems for fraud detection and remediation while balancing fraud loss, cost of implementation, and customer experience Work closely with finance, security, product, research, and trust & safety ope

About the Team OpenAI’s User Operations team shepherds our customers’ adoption of AI and ensures that our customers' product experience is nothing short of exceptional. We are building the very first post-AGI support team. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others, to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role We are looking for an experienced, hands-on support leader to build and run the support and escalation motion for GPT-Rosalind and OpenAI’s life sciences customers. This is both a builder role and a frontline support role. You will work directly with customers, own complex cases, diagnose technical and operational issues, and coordinate cross-functional teams through resolution. You will also create the intake paths, playbooks, knowledge, tooling, and operating mechanisms needed to support life sciences workflows across ChatGPT, Codex, and the OpenAI API. You’ll partner closely with Account Directors, Product, Engineering and Forward Deployed Engineering, Security, Legal, and bioscience subject-matter experts. You will help customers receive coordinated, accurate answers while maintaining clear boundaries between technical support, scientific consultation, product feedback, and roadmap commitments. This role is an opportunity to define how OpenAI supports scientists and life sciences organizations as they adopt increasingly capable AI systems. In this role, you will: Work directly with Rosalind and life sciences customers, taking ownership of complex technical and operational support cases from intake through resolution. Serve as a critical escalation point and final line of defense for complex technical issues, partner

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 looking for an experienced systems software engineer to help define and build the host software stack for our custom next-generation AI systems. You will work close to the hardware on performance-critical software, including Linux kernel drivers, high-throughput I/O paths, and system-scale networking and RDMA. This role spans architecture, implementation, platform bring-up, debugging, and performance optimization. You will work across hardware and software boundaries to make new systems usable end to end, from low-level device interfaces through userspace tooling and production validation. In this role you will: Design, implement, and debug host-side systems software for AI infrastructure, including Linux kernel drivers and supporting userspace components. Build and optimize software paths for high-throughput, low-latency communication, including RDMA and related networking functionality. Develop software around PCIe, DMA, NICs, accelerators, memory movement, and device interaction. Bring up new hardware platforms and diagnose complex issues across kernel, firmware, networking, and hardware boundaries. Build tooling for integration, testing, diagnostics, observability, qualification, and performance characterization. Collaborate with hardware, networking, and platform teams to define interfaces and integrate new capabilities. Work with external vendors where needed to integrate technologies and drive issues to resolution. Contribute across the systems sof

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. Role Overview We are seeking a Package Reliability Engineer to lead reliability engineering for advanced packages used in high-performance AI and computing systems. The primary focus of this role is to assess package level mechanical and thermal reliability risks and apply thermal and mechanical modeling to optimize package design, material selection, and assembly processes. The engineer will also develop reliability test plans with external partners, identify failure mechanisms, perform root-cause analysis, and recommend practical corrective actions. In this role, you will assess package reliability risks from early architecture development through product qualification and high-volume manufacturing. You will work closely with package design, silicon design, system engineering, manufacturing, and ASIC partners to predict package behavior, develop qualification strategies, resolve reliability issues, and improve overall package robustness and lifetime. In this role you will: Lead reliability test plan and assessments for advanced HPC packages, including risk identification, potential failure-mechanism analysis, root-cause investigation, mitigation planning, and corrective-action development. Drive reliability-focused package design optimization based on thermo-mechanical modeling to improve package reliability, power integrity, thermal performance, mechanical robustness, and platform scalability. Develop, validate, and apply package reliability models and lifetime-prediction

About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We operate at the front line of real-world safety and risk management, translating user and operational signals into timely decisions, effective interventions, and improvements to our systems. This role sits on a new team within USRO focused on building operational capacity for new, ambiguous, or fast-moving areas of work. The team helps define what needs to be built, creates the operating model to support it, and works with partner teams to make the work scalable and durable over time. As a Strategic Operations Lead, you will focus on large, cross-functional initiatives that require clear thinking, technical fluency, strong execution, and the ability to bring structure to undefined problems. About the Role We are seeking a Strategic Operations Lead to drive new and existing strategic operating builds across User Safety & Risk Operations. This is a senior IC role for someone who can turn broad, undefined priorities into clear operating models, launch plans, requirements, stakeholder alignment, documentation, reporting, and execution rhythms. This role will often support initiatives where OpenAI is developing new products or partnerships and the operating model is still being defined. These programs have a direct user safety and risk nexus because new deployment models can change what signals OpenAI can see, who owns response decisions, and how user-impacting risks are detected, escalated, and resolved. You will clarify what OpenAI owns, what partner teams own, what signals we can reliably monitor, how issues should be escalated, and how the workflow should evolve from launch support into a durable operating model. The right person is highly strategic and deeply practical. They can move from executive-level framing to detailed workflow design, stakeholder management, SOPs, launch readiness, ri

About the Team The Coding team is reimagining how software is built in the AI era. We build tools and workflows that help software engineers work faster, tackle more ambitious projects, and spend less time on repetitive tasks. AI has already transformed how code is written, but software engineering extends far beyond coding. Our mission is to apply AI across the entire software development lifecycle (SDLC) — from design and implementation to code review, testing, debugging, issue remediation, maintenance, documentation, and user support. The team is also responsible for developer-facing Codex experiences including the Codex IDE Extension and the terminal interface, which are used daily by developers ranging from individual open-source contributors to some of the world’s largest engineering organizations. The team also works closely with the open-source software community, building tools that help maintainers and contributors manage increasingly complex projects. We believe AI can make open-source development more sustainable by reducing the operational burden of reviewing contributions, triaging issues, maintaining quality, and supporting growing communities. By building the future of software development, we're helping advance OpenAI's mission of ensuring that the benefits of AI reach people around the world. About the Role We’re hiring a Full Stack Software Engineer to help invent the next generation of AI-powered software development workflows. “Full stack” in this role means much more than traditional frontend and backend development. You'll own complete product experiences, spanning user interfaces, workflow orchestration, agent and prompt design, backend systems, and cloud infrastructure. This is a highly product-oriented role. You'll work directly on the workflows developers use every day, identifying bottlenecks and rethinking how software gets built in a world where AI agents are active participants in the development process. The features you ship will inf

About the Team OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. About the Role OpenAI is seeking a System Performance Engineer to profile, benchmark, and optimize performance across our embedded hardware products. In this role, you will work across operating systems, applications, camera and vision, graphics, and platform teams to define product KPIs, build performance tooling, and drive optimizations from early lab characterization through product launch and real-world usage. You will help establish the performance standards that shape the user experience of our products, ensuring they remain responsive, efficient, and reliable throughout their lifecycle. This role requires deep expertise in embedded or high-performance systems, strong operating systems fundamentals, and hands-on experience debugging under tight latency, power, and memory constraints. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. In this role, you will: Develop system performance benchmarks, methodologies, and policies to evaluate end-to-end product behavior. Profile and analyze performance across key product use cases and workloads using custom and industry-standard profiling tools. Partner closely with engineering teams to identify bottlenecks and drive performance optimizations across the software stack. Define high-level product KPIs and establish measurement frameworks to measure launch readiness and monitor performance throughout the product lifecycle. Measure, re