Infrastructure Sourcing Operations Lead in San Francisco

About the Team The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. We support critical domains across identity, access, infrastructure security, enterprise systems, and internal productivity. As OpenAI grows, audit readiness and control assurance increasingly depend on reliable data: accurate system inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. Our goal is to move beyond manual evidence collection and build scalable data products, automated validation, and continuous control monitoring that make security and IT controls measurable, repeatable, and defensible. About the Role We are looking for an IT Controls Data Engineer to build the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. In this role, you will design and maintain the pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to turn complex system behavior into reliable control data products. This is a technical builder role. The ideal candidate is strong in data engineering and analytics engineering, comfortable working with enterprise and security system data, and able to explain data lineage, source-system behavior, and control logic clearly to technical and audit stakeholders. You’ll be responsible for Building reliable data pipelines, models, and datasets for IT controls, including access, identity, configuration, change, ticketing, exception, and evidence data. Creating data quality, lineage, reconciliation, and completeness checks that make control data defensible for SOX and other audit use cases. Designing automated evidence generation workflows that produce compl

About the Team The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls. Our work spans data inventory and mapping, classification and lineage, retention and deletion, access governance, purpose and usage controls, auditability, and lifecycle automation. We aim to make policy-aligned data handling the default while giving teams clear, reliable primitives for building and operating products at scale. About the Role We are looking for an experienced Software Engineer to drive the architecture and execution of user data governance across OpenAI. You will define technical direction, build shared platforms and controls, and lead cross-functional programs that make data flows discoverable, policies enforceable, and ownership explicit. This role is well suited to a senior engineer who can move between deep systems design and organization-wide influence, turn ambiguous requirements into pragmatic roadmaps, and operate high-trust systems end to end. This position is based in San Francisco. Relocation assistance is available. In this role, you will: Set the technical strategy and architecture for user data governance across data mapping, classification, lineage, retention, deletion, access, and permitted usage. Design and build shared services, APIs, metadata systems, and policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable. Establish reliable inventories of user data, system ownership, data flows, and policy applicability across products, infrastructure, analytics, and research systems. Partner with Product, Data, Infrastructure, Security, and Legal leaders to define decision rights, translate requirements into controls, and drive adoption across teams. Own governance systems

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 As a software engineer on the Scaling team, you’ll help build and optimize the low-level stack that orchestrates computation and data movement across OpenAI’s supercomputing clusters. Your work will involve designing high-performance runtimes, building custom kernels, contributing to compiler infrastructure, and developing scalable simulation systems to validate and optimize distributed training workloads. You will work at the intersection of systems programming, ML infrastructure, and high-performance computing, helping to create both ergonomic developer APIs and highly efficient runtime systems. This means balancing ease of use and introspection with the need for stability and performance on our evolving hardware fleet. This role is based in San Francisco, CA, with a hybrid work model (3 days/week in-office). Relocation assistance is available. In this role, you will: Design and build APIs and runtime components to orchestrate computation and data movement across heterogeneous ML workloads. Contribute to compiler infrastructure, including the development of optimizations and compiler passes to support evolving hardware. Engineer and optimize compute and data kernels, ensuring correctness, high performance, and portability across simulation and production environments. Profile and optimize system bottlenecks, especially around I/O, memory hierarchy, and interconnects, at both local and distributed scales. Develop simulation infrastructure to validate runtime b

About the Team The Intelligence and Investigations team seeks to rapidly detect and disrupt abuse in AI technologies to ensure their safe use. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits all of humanity. About the Role As an Intelligence Systems Engineer, you’ll be focused on advancing our Intelligence & Investigations efforts at OpenAI, ensuring the safe and responsible use of AI across our products and services. We are seeking a self-starter to prototype, develop, and maintain new tools and processes that integrate OpenAI’s models and infrastructure to enable internal teams to make sense of large, open-domain datasets, fight abuse, and inform high-stakes decisions. You will be a crucial technical bridge between our data scientists and subject matter experts and technical teams like Platform Integrity, Safety Systems, and Research by leading the development of innovative tools and processes that bolster goals in scaled collections, investigations, and analysis. The ideal candidate has strong analytical and data skills, with a background in both prototyping and building scalable systems that can swiftly detect emerging threats, process vast amounts of information, and deliver insights to stakeholders. We value professionals with outstanding communication skills, a commitment to continuous learning, and who are dedicated to promoting the responsible use of AI. 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: Prototype, build, and maintain at-scale intelligence systems that detect, triage, and monitor targeted signals from both open-source and internal data Analyze requirements and deliver end-to-end solutions that address

About the Team The Fleet team builds core components to enable productive research from small to state of the art scale across OpenAI, with the goal of accelerating progress towards AGI. We frequently collaborate with other teams to speed up the development of new state-of-the-art capabilities. About the Role As we scale up with more researchers and engineers joining OpenAI, we seek a pragmatic and passionate engineer with a strong focus on the development experience for both engineers and scientists. In this role, you will be responsible for building and maintaining systems that allow our research + engineering organization to iteratively develop, test, and deploy new features reliably, with high velocity, and with a frictionless and fast development cycle. You will help oversee and drive to the vision of how we should build, test and deploy software. You will drive the design of our continuous integration pipelines, testing infrastructure, training and support around our build system. Our current environment relies heavily on Python, Rust, and C++, which you will take ownership of and strive to transform into a state of the art development experience for research. Ultimately, your role will be to provide the necessary tools and metrics to support our fast-paced culture and ensure a stable, scalable platform for growth, while also fostering a seamless and low friction experience for OpenAI’s research. This role is based in San Francisco, CA. For a San Francisco role, we use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You might thrive in this role if you: Have supported large monorepo development and deployment before Are a proficient Python programmer working in large monorepos Are proficient with Docker and Kubernetes Experienced in CI/CD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boun

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 OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort. The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops. About the Role We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world. We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment. 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: Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security. Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks. Design and iterate on user-facing tools and backend services to support high-quality data workflows Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal r

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 We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. 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. About the Role OpenAI is looking for an experienced Performance Engineer to help us scale the performance, reliability, and efficiency of our systems. In this role, you'll apply deep technical expertise to optimize infrastructure and application-level performance across mission-critical products like ChatGPT and our developer API. You’ll work cross-functionally with teams building core services, training models, and developing real-time user experiences to push our latency, throughput, and cost-efficiency to the next level. We are looking for engineers who thrive in ambiguous environments, value deep systems understanding, and are motivated by delivering measurable impact. This is a highly technical, individual contributor role focused on root-cause analysis, profiling, instrumentation, and architecture-level performance improvements across our stack. In this role, you will: Analyze and optimize performance across application, middleware, runtime, and infrastructure layers—networking, storage, Python runtime, GPU utilization, and beyond. Develop tooling and metrics that provide deep observability into system performance. Collaborate closely with infra, platform, training, and product teams to identify key performance goals and drive systemic improvements. Influence architecture and design decisions to prioritize latency, throughput, and efficiency at scale. Lead investigations into high-impact performance regressions or scalability issues in production. Drive performance testing strategies and help define SLAs/SLOs around latency and throughput for critical systems. You might thrive in this role if you: Have 7+ years of experience in software engineering with a strong tr

About the Team The Strategic Finance team at OpenAI plays a critical role in shaping the company’s long-term trajectory. We partner closely with Product, Engineering, and Go-To-Market teams to inform high-stakes decisions through rigorous data science and economic modeling. As part of our expanding Data Science function, we’re building a best-in-class Forecasting capability to drive real-time, data-driven decision-making across user growth, revenue, compute infrastructure, and more. We are developing scalable forecasting infrastructure to help us understand and anticipate business dynamics in an increasingly complex, usage-based world. Our models are foundational to planning, pricing, operational efficiency, and growth strategy - supporting key investment decisions and unlocking OpenAI’s full potential. About the Role We’re looking for a senior Machine Learning Data Scientist to lead our forecasting initiatives. You’ll be one of the founding members of the Forecasting pillar within Strategic Finance Data Science, responsible for building and scaling robust, interpretable, and production-ready forecasting systems. Your models will power critical business decisions by predicting core metrics such as DAU/WAU, revenue, LTV, compute consumption, and profitability. This is a highly cross-functional role, requiring technical excellence, strong product intuition, and business acumen. You’ll collaborate with product managers, researchers, engineers, and finance leaders to operationalize forecasting insights, influence company-wide strategy, and build foundational forecasting capabilities at OpenAI. 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: Build statistical and machine learning models to solve forecasting needs across product, finance, infrastructure, and GTM domains. Own the end-to-end modeling lifecycle , including scoping, feature engineerin

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 team’s mission is to accelerate the secure evolution of agentic AI systems at OpenAI. To achieve this, the team designs, implements, and continuously refines security policies, frameworks, and controls that defend OpenAI’s most critical assets—including the user and customer data embedded within them—against the unique risks introduced by agentic AI. About the Role As a Security Engineer on the Agent Security Team , you will be at the forefront of securing OpenAI’s cutting-edge agentic AI systems. Your role will involve designing and implementing robust security frameworks, policies, and controls to safeguard OpenAI’s critical assets and ensure the safe deployment of agentic systems. You will develop comprehensive threat models, partner tightly with our Agent Infrastructure group to fortify the platforms that power OpenAI’s most advanced agentic systems, and lead efforts to enhance safety monitoring pipelines at scale. We are looking for a versatile engineer who thrives in ambiguity and can make meaningful contributions from day one. You should be prepared to ship solutions quickly while maintaining a high standard of quality and security. We’re looking for people who can drive innovative solutions that will set the industry standard for agent security. You will need to bring your expertise in securing complex systems and designing robust isolation strategies for emerging AI technologies, all while being mindful of usability. You will communicate effectively across various teams and functions, ensuring your solutions are scalable and robust while working collaboratively in an innovative environment. In this fast-paced setting, you will have the opportunity to solve complex security challenges, influence OpenAI’s security strategy, and play a pivotal role in advancing the safe and responsible deployment of agentic AI systems. You’ll be responsible for: Architecting security controls for agentic AI – design, implement, and iterate on identity, netwo

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role As a Security Engineer on Detection & Response, you’ll help protect OpenAI’s most sensitive assets– including our intellectual property, customer data, and the infrastructure that supports them– by building and operating the systems we use to detect suspicious activity and respond effectively when it matters. You’ll work across endpoints, identity, cloud, hyperscale compute infrastructure, and datacenter-adjacent layers, partnering closely with security teams and infrastructure owners to define the telemetry and response requirements we need and building tooling and automation where it delivers the most leverage. In this role, you will: Build and evolve Detection & Response capabilities across OpenAI’s infrastructure, products, and research environments, with an emphasis on high-signal detection and reliable operational response. Engineer detection pipelines and tooling: develop rule lifecycle management, measurement/quality loops (coverage, precision, latency), tuning processes, and safe rollout patterns. Automate response and investigations by building workflows that reduce toil (triage, enrichment, containment, evidence capture) and improve time-to-understand/time-to-contain. Partner with other Security teams and system/infrastructure owners across the company to ensure new systems ship with the right telemetry, threat models, and response playbooks from day one. Define D&R requirements and drive visibility across endpoin

About the Team The Software Engineering team is responsible for designing and building the scalable, performant, and secure backend systems that power our products—from early prototypes to large-scale deployments. We collaborate closely with product, hardware, and full-stack teams to ensure our infrastructure enables fast iteration while setting a strong foundation for long-term growth. About the Role As a Backend Engineer , you will design and build services, APIs, and infrastructure that support evolving product needs. You’ll apply a deep understanding of backend systems and maintain enough end-to-end context—from hardware to cloud—to guide technical decisions that best serve the product and team. We’re looking for engineers who thrive in fast-paced, collaborative environments and care deeply about building robust systems that scale. 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: Architect, build, and maintain high-performance, secure backend systems. Design APIs, data models, and infrastructure to support evolving product needs. Balance near-term development velocity with long-term maintainability and scalability. Collaborate with cross-functional teams to ensure cohesive, end-to-end solutions. You might thrive in this role if you: Have 7+ years of professional software engineering experience, with a focus on backend systems. Have a proven track record of building and scaling systems from early stage to large scale. Are proficient with Python and Go, and familiar with a range of server-side technologies. Have a strong grasp of system design, performance optimization, and security best practices. Can reason about full-stack tradeoffs from hardware through cloud infrastructure. (Nice to have) Have experience with distributed systems and cloud architectures. (Nice to have) Bring a background in instrumentation, analytics, and performanc

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