Ai Engineering Director in United States

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. 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: Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea

About the Team Our team brings OpenAI’s most capable technology to the world through our developer platform: the OpenAI API. As the leading AI development platform, our API is used by millions of developers and the majority of enterprises around the world, and powers the majority of AI applications that you may use on a daily basis. The platform supports everything from simple model calls to stateful, multimodal, tool-using applications through the Responses API, Agents SDK, Realtime API, and more. Our SDKs turn that fast-moving platform into reliable, idiomatic developer experiences across languages. About the Role We are looking for a software engineer to help build the official SDKs that power the OpenAI API. Currently offered in Python, Node.js, Golang, Java, and Ruby – our SDKs are some of the most popular in the world. You will help shape the developer experience for all new API features, as well as all future versions of our APIs. We’re looking for engineers who are deeply immersed in AI-native development: people who actively build with Codex and other coding agents, have developed agentic applications or developer tools, and bring strong, experience-backed opinions about OpenAI’s APIs. You’ll pair that firsthand product intuition with meticulous SDK design to improve how developers build with our platform. Prior experience building SDKs is lovely, but not absolutely necessary. In this role, you will: Define and implement the SDK experience for all new API features, as well as all future versions of our API. Build and experiment with agentic applications, developer tools, and coding-agent workflows using Codex and OpenAI’s APIs, translating firsthand experience into better SDK abstractions, API ergonomics, and developer experiences. Build and maintain our systems to make SDK maintenance and generation streamlined and automated. Contribute to our SDK strategy and roadmap, including which languages to support and what features to support. Collaborate closely w

About the Team The Hardware Health and Observability team owns the end-to-end health lifecycle of OpenAI’s global compute fleet. Our mission is to maximize healthy, usable compute across accelerator vendors, generations, cloud providers, and regions through reliable health signals, automated remediation, and scalable operational tooling. We build the systems that observe, detect, remediate, and verify hardware issues across GPUs, CPUs, networking, and platform infrastructure, enabling frontier model training and inference workloads to run reliably at hyperscale. We are the last line of defense for the success of OAI’s production and research workloads. About the Role On the Hardware Health and Observability team, you’ll build critical infrastructure that keeps OpenAI’s largest compute clusters healthy and operational at scale. Even small numbers of unhealthy systems can impact large-scale training and inference workloads. This team focuses on minimizing downtime, improving fleet efficiency, and ensuring compute resources remain continuously available to researchers and product teams. Engineers on this team own problems end-to-end, from defining health signals and debugging failures to building automated remediation systems that operate across millions of GPUs globally. In this role, you will: Define and maintain health signals across GPUs, CPUs, networking, and platform infrastructure. Build and evolve health checks that detect, remediate, and verify failures at scale. Ensure critical health checks execute with minimal latency to maximize workload uptime. Investigate hardware failures and system-level issues across large-scale compute environments. Own node lifecycle workflows including drain, quarantine, repair, RMA, and return-to-service processes. Build automation and tooling that enables global cluster management with minimal manual intervention. Partner with workload, reliability, and provider teams to integrate health signals into training and inference system

About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Strategic Sourcing & Procurement function plays a critical role in enabling OpenAI to deliver impact across research, product development, technology infrastructure, and services by helping the company scale responsibly, securely, and with strong commercial discipline. Our work sits at the intersection of innovation and execution. We partner closely with teams across OpenAI to translate rapidly evolving business needs into scalable, compliant, and economically sound external partnerships. As OpenAI continues to grow at pace, services sourcing is becoming increasingly strategic across the company. Every business unit relies on external service providers in different ways — to extend capacity, access specialized expertise, support operations, and accelerate execution. Done well, Procurement becomes a source of trust and momentum, helping OpenAI move faster with the right partners, stronger commercial outcomes, and the right level of protection. About the Role We are seeking an experienced Strategic Sourcing (GTM) Leader to lead strategic sourcing and commercial enablement for OpenAI’s Go-to-Market organization across B2B and B2C channels. You will manage substantial and rapidly growing spend while shaping sourcing strategies and scalable commercial pathways across Media, Creative, Production, Influencer, Agency, Sponsorships, Analytics, Communications, and Event suppliers in support of high-impact global initiatives. You’ll help evolve our GTM procurement function from reactive deal support into a speed-enabling, scalable commercial engine that delivers cost efficiency, launch readiness, and strong governance in a fast-moving environment. In this role, you will: Develop and execute sourcing strategies across GTM, Brand, Global Affairs, Events, Growth, and Partnership activities—spanning both B2B and B2C channels—that align with our mission and b

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you will: Design and run experiments that improve agentic model behavior for complex so

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

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 The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet High Performance Computing (HPC) team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automati

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a researcher focused on our embedding retrieval efforts. You’ll work with a a team of world-class research scientists and engineers developing foundational technology that enables models to retrieve and condition on the right information, at the right time. This includes designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods. This work will support retrieval across many OpenAI products and internal research efforts, with opportunities for scientific publication and deep technical impact. 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. Responsibilities Tackle embedding models and retrieval systems optimized for grounding, relevance, and adaptive reasoning. Collaborate with a team of researchers and engineers building end-to-end infrastructure for training, evaluati

About the Team The RL and Reasoning team drives the core reasoning paradigm and has created groundbreaking innovations such as o1 and o3. They focus on pushing the boundaries of reinforcement learning research, building next-generation generative models, and deploying them at scale. About the Role As a Research Engineer/Research Scientist at OpenAI, you will advance the frontier of AI alignment and capabilities through cutting-edge RL methods. Your work will sit at the heart of training intelligent, aligned, and general-purpose agents, including the systems that power various models. We’re looking for people who have a background in reinforcement learning research, are able to iterate quickly, and are proficient at coding. 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. You might thrive in this role if: You love being on the cutting edge of RL and language model research. You’re a self-starter who takes initiative and ownership of ideas, driving them to completion. You value principled approaches, simple experiments in tightly-controlled settings, and reaching trustworthy conclusions which stand the test of time. You thrive in a fast-paced, dynamic, and technically complex environment where rapid iteration is key. You’re comfortable diving into a large ML codebase to debug and improve it. You have a deep understanding of machine learning and machine learning applications. 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 boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the ful

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet Hardware team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automation to reduce manual work

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 operational in how we execute, and we support every product and research effort at OpenAI. Our tenets include prioritizing for impact, enabling researchers and developers, preparing for future transformative technologies, and fostering a strong, collaborative security culture. About the Role OpenAI is seeking a Security Software Engineer to join the Infrastructure Security (InfraSec) team. InfraSec safeguards the core of OpenAI’s research and production environments—GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter spans everything from bare-metal hardware and firmware to Kubernetes clusters, service meshes, and the data pathways that carry highly sensitive model weights and user data. As a Security Software Engineer, you will design and build critical foundational services, such as authentication systems, egress/ingress proxies, access brokers, and key management platforms, that demand high standards of reliability, scalability, and software craftsmanship. These systems form the security backbone of OpenAI’s supercomputing environment and must remain robust under intense scale and adversarial pressure. In this role, you will: Architect and implement production-grade security services (e.g., auth services, access brokers, secure proxies, key-management infrastructure) that provide strong guarantees across hardware, operating systems, Kubernetes, networks, and CI/CD. Partner with infrastructure and research engineers to embed security into high-performance compute clusters, enabling rapid model training and deployment without compromising protection. Develop automation and detection tooling to continuously identif

About the Team We’re hiring software engineers to make the Workload team more productive. The Workload team maintains the core components of OpenAI’s training and inference frameworks and helps execute frontier experiments. About the Role We’re looking for someone who cares about the developer experience of working in and around OpenAI’s core training and inference frameworks. In this role you will: Be responsible for optimizing the development workflows of the engineers around you Work within various Workload teams to address their specific needs, but collaborate with the centralized teams that own various aspects of development experience Optimize iteration speed, both broadly, and in particular by optimizing specific teams’ CI Improve reliability, for instance, by driving testing strategy for particular components Work through the long tail of things that it takes to build libraries and systems that will delight researchers You might thrive in this role if: You are motivated by helping people. You believe a thing that separates great teams from good teams are the players willing to do whatever work it takes, without ego. You believe in the power of developer experience. Something magical happens when people can quickly and confidently iterate on a simple codebase, but this magic is fragile and must be fought for. When you see someone trip over something, no matter how small, your first instinct is asking yourself what it would take for that to not happen again. Your second instinct is clicking merge on the PR you’ve already written to make it so. You are pragmatic. You have the ability to see the world through a perfectionist’s eyes, but are not yourself a perfectionist. You know which problems to pick and when to switch to making progress on a different problem. You like going end-to-end on things. You love co-design — that feeling when you were only able to find the right solution because you both deeply understand the users that interact with a system and the

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are hiring a Sim Infrastructure Engineer to turn simulation systems into reliable, automated, production-quality pipelines that power model training, evaluation, and hardware-in-the-loop validation. This role owns the automation, orchestration, and tool integration that apply simulation to concrete robotics tasks: building CI/CD for SIL/HIL, presubmit checks, automatic model evaluation, metric computation and reporting, and the runtime infrastructure to run simulations at scale. You will collaborate closely with Sim Realism, Sim Environments, Research, and Ops to make simulation an integrated, reproducible, and measurable part of our ML and robotics workflows. This role is based in San Francisco, CA, and requires in-person 4 days a week. In this role, you will: Build and maintain presubmit checks, continuous integration and deployment pipelines for simulation code, environments, and tasks so simulation artifacts are testable, versioned, and reproducible. Implement end-to-end automation to run model evaluation in sim (SIL) and orchestrate HIL runs; compute realism and task metrics, generate dashboards and alerts, and ensure evaluation is repeatable and auditable. Create robust APIs and connectors so research, training, and data-collection systems can schedule, seed, and evaluate batches of simulations; support RL rollouts, imitation-data collection, and presubmit model checks. Build scheduling, batching and orchestration for running very large numbers of concurrent rollouts (target tens of thousands of rollouts / large RL workloads), sol

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, Application Security you will be responsible for identifying and mitigating security vulnerabilities within software applications through building security tools, code reviews, penetration testing, and security assessments. We’re looking for people who will work closely with development teams to ensure secure coding practices are integrated throughout the software development lifecycle, preventing security risks before they emerge. You will also provide security guidance to developers and other stakeholders, fostering a culture of security awareness within the organization. The role is preferred to be based in San Francisco, Seattle or New York City but may consider remote work. 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: Perform Security Assessments : Conduct regular security assessments, code reviews, and penetration testing to identify vulnerabilities in applications and software. Develop and Implement Security Tools : Design, develop, and implement security tools, frameworks, and methodologies to protect applications against security threats. Collaborate with Development Teams : Work closely with development teams to ensure security best practices are integrated throughout the software development lifecycle (SDLC), including secure coding guidelines. Threat Modeling and Risk Assessment : Conduct threat modeling and risk