Product Management Lead in San Francisco

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

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the Role We are looking for customer-focused software engineers to build effective custom software that leverages OpenAI’s APIs to solve real customer problems. As an FDSWE, you will work with our customers and OpenAI Forward Deployed Engineers to design and implement scalable solutions that solve their most difficult problems. You will design abstractions to solve customer problems, and then use them to scale our speed and quality of delivery across all Forward Deployed engagements. You will collaborate closely with Sales, Solutions Engineering, Solutions Architects, and Customer Success Managers who work on the same account. You will also work with our Research and Applied Product and Engineering teams to provide insightful customer feedback. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will: Embed deeply with strategic customers to understand their business challenges and technical requirements in detail. Design, architect, and develop full-stack solutions using an experiment-driven, iterative approach. Prepare detailed scopes of work and project plans for both proof-of-concept prototypes and full production deployments. Work hands-on with customers' technical teams as a technical expert and trusted advisor, coding side-by-side to drive projects to completion on their infrastructure. Collaborate with Product, Research and Applied teams to ensure seamless customer experiences, project success and actionable product feedback Contribute to internal knowledge bases, codifying best practices and sharing insights gained from customer engagements to scale the Forward Deployed Engineering function. You’ll thrive in th

About the Team The AI Architect team partners with organizations to turn OpenAI's most capable models into meaningful, real-world impact. We work with customers across industries and digital-native businesses to identify where AI can create value, design secure and scalable solutions, and help those solutions move from early exploration into sustained production adoption. The team brings together technical strategy, customer partnership, and practical deployment expertise, working closely with Sales, Product, Engineering, Research, and specialist delivery teams. About the Role As an AI Architect, you will be the senior technical owner for a named portfolio of customers and the primary technical counterpart to their leadership teams. You will act as the “CTO of your book of business”, shaping each customer's AI strategy and guiding their journey from pre-sales discovery and solution evaluation through deployment, adoption, and measurable business impact. You will own the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex, and other agentic AI solutions. In partnership with the Account Director, you will translate business priorities into a focused use-case portfolio, an actionable adoption roadmap, and a clear path to durable customer value and growth. The Account Director owns commercial strategy; you own the technical strategy, customer journey, and path to production value. You will remain accountable for the technical outcome while bringing in the right specialists across deployment, implementation, enablement, security, product, and partners to provide deeper expertise and execute work where needed. This role calls for strong industry fluency, sound architectural judgment, and the ability to move confidently between executive strategy and hands-on technical conversations. In this role, you will: Serve as the primary technical advisor and long-term technical relationship owner for a named portfolio of existing customers and pre-sales prospect

About the Team The Business Data Science team uses data and analytics to optimize business performance, drive growth, and foster meaningful partnerships, with the goal of ensuring the sustained and impactful expansion of OpenAI's initiatives to maximize the benefits of AGI for all of humanity. We partner with Sales (GTM), Marketing, Partnerships, Support, Finance, Product, and Growth. About the Role As a member of our Business Data Science team, you will help build a data-driven culture around insight generation, decision making, and strategy at OpenAI. This role is focused on driving customer success within our business products (ChatGPT Team, ChatGPT Enterprise, and API). You will work on projects such as identifying opportunities for interventions within a customer lifecycle to drive activation & onboarding, identifying target audiences for new feature launches, and measuring the efficacy of emails, events, and other interventions to drive ongoing engagement with our products. This role is based in San Francisco, CA or New York, NY. 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: Embed with our Customer Success organization as a trusted partner, uncovering new ways to drive customer adoption and engagement of our business products. Establish key metrics, run experiments, and perform analysis to help us understand the incrementality of our efforts to drive adoption/engagement. Proactively surface insights and opportunities to drive engagement and growth. Build tools and systems for stakeholders to self-serve routine data and insights freeing up time to work on more leveraged analyses. Become an expert in OpenAI’s data and systems. Through partnership with Data Eng, Finance and other business teams, you will self-serve all the underlying data for our business and derive insights from them. Partner with other data scientists across the company to share knowledge and continually

About the Team OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products—pricing & packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner with Product, Engineering, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. About the Role As a Data Scientist on FinEng, you’ll own the analytics and experimentation that improve our checkout and payments , subscriptions , and pricing & monetization systems. You’ll define the metrics that matter, build the source-of-truth data assets, and design experiments that increase conversion, reduce churn and payment failures, and expand global payment method coverage. Your work will directly influence revenue, customer experience, and how we scale internationally. 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 Own checkout & payments analytics and experimentation across methods and locales (e.g., bank transfers, emerging rails), improving conversion while monitoring risk and latency. Build and run the experimentation program for in-house checkout—define success metrics and guardrails, execute staged rollouts, and use offline incrementality when online tests aren’t feasible. Create operational visibility and source-of-truth data with FinEng Data Engineering—land team-level metrics, SLAs, and self-serve dashboards that drive proactive action. Lead subscription, retention, and monetization analytics—ship launch-readiness for new subscription features, reduce involuntary churn (e.g., targeted retrials/nudges), and develop elasticity/FX frameworks toward pricing optimality. You might thrive in this role if you have 5+ years in a quantitative role (data science, product analytics, or experimentation) in high-growth or fintech environments Fluency in SQL and Python ,

About the Team: OpenAI's mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. Our API is the industry's most widely adopted AI platform, empowering startups, indie developers, and Fortune 500 companies alike. Through multimodal APIs—spanning real-time interactions, text-to-speech (TTS), speech generation, and image generation—we enable users to harness the full potential of diverse AI modalities effectively and at scale. About the Role: We are seeking an Engineering Manager to lead our multimodal API product suite. Your team will be responsible for delivering innovative APIs across real-time processing, speech transcription, speech generation, and image creation. You will own the product roadmap for how we evolve our multimodal API offerings, and you will build the products that allow developers to reach millions of end users through AI audio, video, and images. In this role, you will: Build, mentor, and grow a high-performing engineering team focused on multimodal API products – including our realtime API, our transcription models (Whisper), our speech generation models (TTS), and our image generation APIs (DALLE and native 4o). Collaborate closely with product managers, designers, and other stakeholders to define the strategic vision and product roadmap. Work closely with our research teams to improve our core multimodal models for API customer use cases. Guide technical and architectural decisions, emphasizing scalability, robustness, and user experience. Foster a culture of innovation, continuous improvement, and accountability within your team. Qualifications: Proven experience managing engineering teams that deliver complex, high-quality products at scale. Strong technical background and proficiency in modern software engineering practices and system architecture. Excellent collaboration and communication skills to effectively coordinate across diverse teams and stakeholders. Familiarity with or strong interest in multimoda

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, governance, and enterprise capabilities that help Codex spread across developers, teams, and organizations worldwide. The Enterprise Controls team owns the systems that allow companies to safely deploy Codex across their organization while protecting their most sensitive code, data, and internal knowledge. About the Role As Codex adoption grows inside large organizations, customers are increasingly trusting Codex with their most valuable assets: proprietary codebases, internal documentation, customer data, and sensitive workflows. This role will help build the enterprise control plane that makes Codex secure, governable, and trustworthy at scale. You will design and operate backend systems that give enterprise administrators visibility and control over how Codex is used across their organization. You will work across identity, access, encryption, policy enforcement, auditability, and admin controls. This may include systems that let customers manage encryption keys, control which Codex capabilities are enabled, enforce organizational policies, and understand how data flows through Codex. This role owns systems end-to-end: from architecture and

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for a Backend Software Engineer to help architect and scale the infrastructure that powers our knowledge systems. 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. In this role, you will: 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 product, research, and engineering teams to integrate OpenAI mode

About the Team The User Operations team (Support) is central to ensuring that our customers' experience with our products is nothing short of exceptional. 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 seeking a dynamic support strategy operator to drive strategic and operational initiatives across OpenAI’s customer support/user operations landscape. In this role, you will work closely with leaders in User Operations and across the company to help scale, mature, and optimize our support operations. Your work will span a range of strategic initiatives aimed at enhancing the customer experience and driving operational excellence, ensuring that our support organization can sustainably scale with the business's growth. You’ll be responsible for deeply understanding our organization and priorities – where we’re at, where we’re going – and will work relentlessly towards planning and executing on our vision to provide best-in-class support. This role is not “creating and executing playbooks”. AI has and will continue to fundamentally change the customer experience and the way we build tools and organizations; this role requires a proactive, strategic planner and executor that can think ten steps ahead, defining the future of customer support at OpenAI and in the world. In this role, you will: Drive the ideation and operationalization of new support systems, processes, and programs. Collaborate with leaders to identify, evaluate, and prioritize new strategic and operational initiatives, ensuring alignment with company goals and unique organizational objectives Work with product, enginee

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. We believe that achieving our goal requires real world deployment and iteratively updating based on what we learn. The Protection Scientist Engineer, Integrity team supports this by identifying and investigating misuses of our products – especially new types of abuse. This enables our partner teams to develop data-backed product policies and build scaled safety mitigations. Precisely understanding abuse allows us to safely enable users to build useful things with our products. About the Role Protection Science Engineering is an interdisciplinary role mixing data science, machine learning, investigation, and policy/protocol development. As a Protection Scientist Engineer within Integrity and Investigations, you will be responsible for designing and building systems to proactively identify and enforce on abuse on OpenAI’s products. This includes ensuring we have robust abuse monitoring in place for new products, sustaining monitoring for existing products, and prototyping and incubating systems of defense against our highest risk harms. You will also respond to and investigate critical escalations, especially those that are not caught by our existing safety systems. This will require expert understanding of our products and data, and involves working cross-functionally with product, policy, and engineering teams. This role can be based in either our San Francisco, or NY office and includes participation in an on-call rotation that will involve resolving urgent escalations outside of normal work hours. Some investigations may involve sensitive content, including sexual, violent, or otherwise-disturbing material. In this role, you will: Scope and implement abuse monitoring requirements for new product launches. Improve processes to sustain monitoring operations for existing products, including developing approaches to automate monitoring subtasks. Prototyp

About the Team OpenAI’s Inference team powers the deployment of our most advanced models - including our GPT models, 4o Image Generation, and Whisper - across a variety of platforms. Our work ensures these models are available, performant, and scalable in production, and we partner closely with Research to bring the next generation of models into the world. We're a small, fast-moving team of engineers focused on delivering a world-class developer experience while pushing the boundaries of what AI can do. We’re expanding into multimodal inference, building the infrastructure needed to serve models that handle image, audio, and other non-text modalities. These workloads are inherently more heterogeneous and experimental, involving diverse model sizes and interactions, more complex input/output formats, and tighter coordination with product and research. About the Role We’re looking for a software engineer to help us serve OpenAI’s multimodal models at scale. You’ll be part of a small team responsible for building reliable, high-performance infrastructure for serving real-time audio, image, and other MM workloads in production. This work is inherently cross-functional: you’ll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. You'll build and optimize the systems that let users generate speech, understand images, and interact with models in ways far beyond text. In this role, you will: Design and implement inference infrastructure for large-scale multimodal models. Optimize systems for high-throughput, low-latency delivery of image and audio inputs and outputs. Enable experimental research workflows to transition into reliable production services. Collaborate closely with researchers, infra teams, and product engineers to deploy state-of-the-art capabilities. Contribute to system-level improvements including GPU utilization, tensor parallelism, and hardware abstraction layers. You might thrive in t

About the Team The Developer Experience team at OpenAI has a singular focus: empowering developers globally. Our mission is to provide every developer and startup on the planet with the most delightful and seamless experience to integrate AI into their applications and products. We ensure developers have the tools, resources, and support they need to unlock AI’s full potential. We create inspiring demos, developer tools, sample applications, and technical content that show developers how to build with Codex and frontier models like GPT-5.6, GPT-Live, and GPT-Image-2 to create powerful agents and AI-native applications. We collaborate closely with product, engineering, research, and GTM teams to ensure the developer journey, from onboarding with Codex to first API call to production deployment, is seamless, effective, and delightful. About the Role As a Developer Experience Engineer, you will create compelling technical content, developer tools, and sample applications designed to inspire developers and enable them to succeed with Codex and OpenAI’s APIs and products for developers. You will engage with developers and technical founders, demonstrating best practices and building innovative applications powered by frontier models, multimodal capabilities, and tools like Codex. We’re looking for people who combine strong technical skills, creativity, and a passion for engaging with and empowering developers. In this role, you will: Develop demos and sample applications that showcase best practices for building with Codex, frontier models, multimodal capabilities, and agents. Create high-quality technical content—including tutorials, blog posts, videos, and code samples—to educate and inspire the developer community about our models, APIs, and Codex. Actively engage with and foster a vibrant local and global developer ecosystem around OpenAI’s platform and products. Represent OpenAI at developer events and online, serving as a knowledgeable and approachable advocate for

About the Team The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software is reliable, testable, and ready to ship. We design and maintain automated test frameworks, hardware-in-the-loop labs, and release pipelines that keep quality signals trustworthy and enable rapid, safe product launches. Our work spans developer tools, automation, systems integration, and cross-team collaboration to ensure every release meets the highest standards. About the Role As a Software Engineer, Quality and Developer Tools , you will build and own the systems that validate our device software—from test frameworks and regression infrastructure to hardware-in-the-loop labs and release gates. You’ll design the tooling and automation that keep quality signals trustworthy, integrate them into CI/CD, and make it easy for engineers and QA vendor technicians to execute reliable, repeatable workflows. We’re looking for engineers with deep experience in software quality, automation, developer tooling, and hardware-software integration who thrive on building scalable, reliable systems for validation and release readiness. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. In this role, you will: Test infrastructure & frameworks: Design, implement, and maintain a unified test framework for device software across unit, integration, system, and end-to-end testing, with reproducible runs and integrations with GitHub, Linear, and Slack. CI/CD integration & releases: Integrate test suites with Buildkite, enforce promotion criteria for staging and production, auto-file regressions, and publish traceable artifacts and release notes. Hardware-in-the-loop lab design & orchestration: Plan and bring up racks, power and networking systems, and orchestration for device testing; support automated flashing, provisioning

About the Team The Applied team at OpenAI safely brings cutting-edge technology to the world. We have released widely used products such as ChatGPT, Sora, and the OpenAI API, powering models including GPT-5 and a growing set of multimodal capabilities across text, image, audio, and video. Our team also manages large-scale inference and platform infrastructure that supports these experiences at global scale. With much more on the horizon, our impact continues to grow. Our customers build fast-growing businesses using our APIs, unlocking product capabilities that were previously unimaginable. ChatGPT and Sora exemplify the breadth of what’s now possible across text, image, audio, and video experiences. As these capabilities expand, we prioritize the responsible use of our technology, emphasizing safe and thoughtful deployment over unchecked growth. Within Applied Engineering, the Ads Monetization team in Financial Engineering builds the core systems dealing with all the money flows for ChatGPT Ads. These systems are a combination of low-latency, high scale, high reliability, while being built in a financially correct, accurate, auditable and explainable way. This role sits at the intersection of ads delivery, data engineering, and financial systems. In this role, you will: Architect and build the core monetization systems for ChatGPT Ads. Build and operate the core services and pipelines that power ads monetization end-to-end, from event capture and validation through aggregation, pricing, metering, and ultimately producing billable outputs. Define and implement the source of truth for ads monetization data, including schemas, data models, and invariants that ensure outputs are consistent, explainable, and auditable. Own correctness and reconciliation: align production outputs with downstream invoicing/finance requirements, build controls/monitors, and close gaps through investigations and backfills. Develop across the stack to create comprehensive billing integration