Internal Communications in San Francisco

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 Full Stack software engineers with a product mindset to join the GTM Innovation team. As a product engineer on this 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-s

About the Team The Support Automation team at OpenAI scales the organization by applying cutting-edge AI models to real-world challenges, automating and enhancing work across the organization. From customer operations to engineering, we develop an ecosystem of automation products that empower our colleagues and drive impact. We're passionate about crafting products that serve those around us, blending rapid prototyping with a focus on long-term quality and reliability. By creating reusable solutions, we create patterns that can be applied across diverse domains within OpenAI. TLDR: this team leverages OpenAI technology to improve OpenAI, and you’ll have the opportunity to leverage the full extent of our tech (both public and pre-released) to accomplish this mission. About the Role We’re looking for a Backend Software Engineer with experience working in ML/LLM-heavy domains to help to design and build an evals infrastructure that measures the quality of OpenAI’s support automation. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. The role will especially focus on working closely with Data Science and Research partners to design and build evals at scale. In this role, you will: Design eval pipelines that are reliable, reproducible, and extendable Build the infrastructure for continuous eval monitoring frameworks (regression/drift monitoring, building robust golden datasets) along with feedback loops that ultimately strengthen support automation Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. Collaborate closely with data, research, and engineering teams to integrate OpenAI models into high-leverage workflows

About the Team The Privacy Engineering Team at OpenAI is committed to integrating privacy as a foundational element in OpenAI's mission of advancing Artificial General Intelligence (AGI). Our focus is on all OpenAI products and systems handling user data, striving to uphold the highest standards of data privacy and security. We build essential production services, develop novel privacy-preserving techniques, and equip cross-functional engineering and research partners with the necessary tools to ensure responsible data use. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing AGI that offers widespread benefits. About the Role As a part of the Privacy Engineering Team, you will work on the frontlines of safeguarding user data while ensuring the usability and efficiency of our AI systems. You will help us understand and implement the latest research in privacy-enhancing technologies such as differential privacy, federated learning, and data memorization. Moreover, you will focus on investigating the interaction between privacy and machine learning, developing innovative techniques to improve data anonymization, and preventing model inversion and membership inference attacks. This position is located in San Francisco. Relocation assistance is available. In this role, you will: Design and prototype privacy-preserving machine-learning algorithms (e.g., differential privacy, secure aggregation, federated learning) that can be deployed at OpenAI scale. Measure and strengthen model robustness against privacy attacks such as membership inference, model inversion, and data memorization leaks—balancing utility with provable guarantees. Develop internal libraries, evaluation suites, and documentation that make cutting-edge privacy techniques accessible to engineering and research teams. Lead deep-dive investigations into the privacy–performance trade-offs of large models, publishing insights that inform model-training and prod

About the Team Business Marketing at OpenAI helps companies understand, adopt, and realize value from intelligence at work. We believe our own marketing organization should demonstrate what changes when intelligence becomes part of the work: fewer manual handoffs, faster learning, better use of customer and product signals, and more capacity for ambitious thinking. Marketing Technology works across Marketing, go-to-market, Data, Engineering, IT, Security, and Product to define the systems, agents, data, workflows, and operating model that power modern marketing at OpenAI. The team has an opportunity to rethink marketing operations alongside the people building the models, products, and infrastructure shaping the future of AI. About the Role We are hiring a Head of Marketing Operations & Technology to build the most AI-enabled marketing operations organization in the world. You will own the systems, infrastructure, data, and workflows that help Marketing operate with greater intelligence, speed, and impact. You will set the function’s strategy, decide what to build or buy, and develop new capabilities where existing solutions fall short. This role sits at the intersection of marketing, technology, data, and AI. You will partner closely with Engineering, Product, Sales, Growth, and Revenue Operations while building a team of technical operators and builders who can turn ambitious ideas into dependable systems. We welcome varied backgrounds—from marketing operations leaders who have expanded the function’s traditional boundaries to founders and builders of AI-native products, growth infrastructure, or internal platforms. What matters most is a deep understanding of marketing, strong technical instincts, and the ambition to imagine a fundamentally better way of working. In this role, you will: Define the vision, strategy, and operating model for Marketing Operations & Technology, including how AI should reshape the function. Build and lead a team spanning market

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the core infrastructure behind OpenAI’s monetization and ads systems. In this foundational role, you’ll architect and implement distributed systems that power OpenAI’s monetization stack—focusing on reliability, performance, privacy, and large-scale operation. You’ll work across backend, systems, and platform layers to define and implement 0→1 infrastructure, partnering closely with Product, Design, and Research to shape the future of monetized AI experiences. Your work will enable both internal and external teams to build on safe, scalable, and robust monetization primitives. This role is exclusively based across our San Francisco & Seattles sites. We offer relocation assistance to new employees. In this role, you will: Design and build the foundational backend and infrastructure powering OpenAI’s monetization and ads systems Architect large-scale distributed systems that

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 Sales team has a unique mission to help customers understand the deep impact that highly capable AI models can bring to their business and users. This role is a mixture of technical understanding, vision, partnership, and value-driven strategy. You’ll be a key driver of opportunities through the entire sales cycle, from pipeline generation to closure. You’ll work with researchers, engineers, and solution strategists to help customers evolve their industry with AI. This role can be based in our San Francisco or Seattle offices. We are also considering applications to work remotely from within the U.S. 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'll: Manage ~five key accounts, developing and executing strategies for a comprehensive account plan Lead our enterprise customers’ journeys from ideation to successful deployment Partner with solutions and research engineering to build and execute complex customer programs and projects Own a consumption revenue target Manage consumption revenue forecasts Analyze key account metrics to create reports and provide insights to internal and external stakeholders Closely monitor the industry landscape (people, competitors, partners, etc.) to contribute to product roadmap and other corporate strategies Collaborat

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 Operations Program Manager (OPM) to serve as the single-threaded operational leader for new hardware introductions (NPI) and production ramps across OpenAI’s AI infrastructure systems. This role combines hands-on execution with strategic ownership. You will be responsible for defining the operating model, aligning cross-functional stakeholders, setting the critical path, making informed tradeoffs, escalating decisively, and ensuring hardware programs deliver on schedule, quality, cost, and scalability. Success in this role requires comfort operating in ambiguity, influencing without authority, and driving alignment across internal teams and external partners—while keeping eyes firmly on long-term system scalability and repeatability. In this role, you will: Strategic & Leadership Ownership Act as the single-threaded owner for operational readiness across NPI and ramp, accountable for outcomes from early bring-up through sustained production Translate OpenAI’s infrastructure strategy and engineering objectives into clear operating plans, execution priorities, and decision frameworks Drive alignment across Engineering, Operations, Strategic Sourcing, Finance, Capacity Planning, and Executive stakeholders by framing tradeoffs, risks, and recommendations Proactively identify inflection points where decisions or investments are required to protect long-term scale, reliability, or cost targets Influence operational strategy with manufacturing par

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

About the Team OpenAI's Legal team plays a crucial role in furthering OpenAI's mission by tackling innovative, fundamental legal issues in AI and supporting OpenAI’s growth. If you're passionate about doing significant and unique work, this team is for you. The team comprises professionals from diverse fields, including technology, AI, privacy, IP, corporate, employment, tax law, regulatory, and litigation. About the Role As a Senior Corporate Counsel, M&A, you will support and lead mergers, acquisitions, joint ventures, investments, warrants, infrastructure financings and other corporate transactions through the full lifecycle and provide strategic advice to the business on a broad range of transactional matters. This is a unique opportunity to be directly involved in the forefront of the legal and technology field. This role will work closely with our Corporate Development, Finance, Product & Research, People, and other teams and report to our Deputy General Counsel, M&A, Investments and Strategic Transactions. 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: Lead and support mergers, acquisitions, joint ventures, investments, partnerships and other strategic transactions through the full lifecycle, including opportunity assessment, deal structuring, negotiation, due diligence, and execution Draft, review, and negotiate transaction documents, including definitive agreements, letters of intent, and ancillary documents. Provide strategic advice to the corporate development team, senior management and other internal stakeholders regarding transactions and M&A strategy and deal execution. Work collaboratively with multiple cross-functional teams across the company, including on post-transaction and integration matters. Support the corporate legal team on a broad range of corporate matters, including financings, liquidity events,

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 an experienced Optical Network Engineer to lead Laser related work within our optical interconnect efforts for large-scale compute systems. The role also requires broad, hands-on optical validation experience across IM/DD-based interconnects, working from lab characterization through production readiness and scaled deployment. In this role you will: Drive laser-focused requirements and technical direction within the broader optical interconnect roadmap. Lead evaluation and validation of optical components and subsystems, including laser-based elements, in lab and production-representative environments. Support end-to-end optical testing for IM/DD interconnects (e.g., module/system bring-up, characterization, debug, and readiness for scale). Work with external partners to align on development milestones, performance targets, and quality expectations. Own technical issue triage and resolution across performance, reliability, and manufacturability topics. Collaborate across internal teams to support integration, rollout, and operational success at scale. You might thrive in this role if you have: Strong experience in laser-focused optical engineering (development, validation, manufacturing readiness, or field support). Broad hands-on background with IM/DD optical technologies and optical test/debug workflows. Experience working with external suppliers/manufacturing partners and production-oriented execution. Demonstrated ability to debug complex t

About the Role The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production. We own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous. This role sits at the intersection of developer productivity, distributed systems reliability, and large-scale infrastructure orchestration. In This Role, You Will Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback. Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows. Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale. Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns. Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks. Build systems that support agent-assisted or autonomous deployment workflows using modern AI tooling. Technologies commonly used in this environment include: Kubernetes for large-scale container orchestration and runtime infrastructure Python and FastAPI for internal services Terraform for infrastructure as code GitOps-based deployment workflows (e.g., ArgoCD, Flux, or similar systems) Buildkite for CI orchestration You may be a strong fit if you: Have worked with Kubernetes-based deployment systems at scale Have experience building or operating continuous deployment platforms Are familiar with GitOps tooling such as

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with research, software, and external hardware partners to shape the next generation of AI systems, from silicon through full-scale deployments. Our team focuses on understanding and optimizing performance across the full system stack—ensuring that architectural decisions are grounded in rigorous, quantitative analysis of real-world workloads. About the Role We are seeking a Performance Modeling Lead to build and lead a small, high-impact team responsible for answering forward-looking architectural questions across AI infrastructure systems. You will develop modeling frameworks and methodologies to evaluate system-level tradeoffs and guide key design decisions. Your work will directly influence reference architectures, vendor designs, and long-term infrastructure strategy. This role sits at the intersection of AI workloads, system architecture, and quantitative modeling, and requires strong technical judgment, ownership, and the ability to translate complex analysis into clear, actionable guidance. 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. Key Responsibilities Build and own a performance modeling framework/toolchain to evaluate AI systems across multiple levels of abstraction. Analyze and quantify architectural tradeoffs across compute, memory, networking, storage, and system topology. Develop performance models to guide decisions on: scale-up vs. scale-out architectures interconnect and network design memory hierarchy and system balance. Translate modeling outputs into clear recommendations for internal teams and external hardware vendors. Influence reference designs and vendor roadmaps through data-driven insights. Partner closely with machine learning, systems, and hardware teams to understand workload characte

About the Team The Future of Computing Research team is an applied research team in the Consumer Devices group focused on developing new methods and models to support our vision as we advance forward in our mission of building AGI that benefits all of humanity. About the Role As a Technical Lead on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. This role is based in San Francisco, CA. We follow a hybrid model with 3 days a week in the office and offer relocation assistance to new employees. In this role, you will: Evaluate and select silicon platforms (GPUs, NPUs, and specialized accelerators) for on-device and edge deployment of OpenAI models. Work closely with research teams to co-design model architectures that meet real-world deployment constraints such as latency, memory, power, and bandwidth. Analyze and model system performance, identifying tradeoffs between model design, memory hierarchy, compute throughput, and hardware capabilities. Partner with hardware vendors and internal infrastructure teams to bring up new accelerators and ensure efficient execution of transformer workloads. Build and lead a team of engineers responsible for implementing the low-level inference stack, including kernel development and runtime systems. Run through the necessary walls to take nascent research capabilities and turn them into capabilities we can build on top of. You might thrive in this role if you: Have experience evaluating or deploying workloads on GPUs, NPUs, or other specialized accelerators. Understand the performance characteristics of transformer models, including attention, KV-cache behavior, and memory bandwidth requirements. Have designed or optimized high-performance compute systems, such as inference engines, distributed runtimes, or hardware-aware ML pipelines. Have experience building or leading teams work

About the Team OpenAI’s Stargate and 3P Engineering teams are responsible for building and scaling the external infrastructure ecosystem that powers advanced AI systems. We work across hyperscalers, colocation providers, cloud partners, and strategic third-party operators to turn contracted capacity into production-ready compute. Our scope spans the full lifecycle of external deployments: commercial alignment, technical readiness, network integration, hardware enablement, operational readiness, and long-range scaling strategy. As OpenAI’s infrastructure footprint expands globally, we need leaders who can convert complex partner environments into reliable, high-velocity capacity for training and inference workloads. About the Role We are seeking a Technical Program Manager, Token-as-a-Service (TaaS) to lead delivery of external compute capacity that directly serves OpenAI model workloads. In this role, you will own complex cross-functional programs that transform third-party infrastructure into usable tokens at scale. You will partner across engineering, capacity planning, networking, hardware, finance, product, and external providers to ensure that deployed capacity translates into real production throughput. This role sits at the intersection of infrastructure execution, systems readiness, and business impact. Success requires strong technical fluency, elite program management, and the ability to drive accountability across internal teams and external partners. This is a high-visibility role with direct impact on OpenAI’s ability to scale model training and inference globally. This role is based in San Francisco, CA, with a hybrid work model of 3 days in office per week. Relocation assistance is available. Key Responsibilities Lead end-to-end delivery programs that convert external infrastructure capacity into production-ready token supply. Own readiness across compute, storage, networking, security, and operational dependencies for third-party environments. Build