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About the Team At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure. The Caching Infrastructure team is responsible for building a caching layer that powers many critical use cases at OpenAI. We aim to provide a high-availability, multi-tenant cache platform that scales automatically with workload, minimizes tail latency, and supports a diverse range of use cases. We’re looking for an experienced engineer to help design and scale this critical infrastructure. The ideal candidate has deep experience in distributed caching systems (e.g., Redis, Memcached), networking fundamentals, and Kubernetes-based service orchestration. In This Role, You Will: Design, build, and operate OpenAI’s multi-tenant caching platform used across inference, identity, quota, and product experiences. Define the long-term vision and roadmap for caching as a core infra capability, balancing performance, durability, and cost. Collaborate with other infra teams (e.g., networking, observability, databases) and product teams to ensure our caching platform meets their needs. You Might Thrive In This Role If You: Have 5+ years of experience building and scaling distributed systems, with a strong focus on caching, load balancing, or storage systems. Have deep expertise with Redis, Memcached, or similar solutions, including clustering, durability configurations, client-side connection patterns, and performance tuning. Have production experience with Kubernetes, service meshes (e.g., Envoy), and autoscaling systems. Think rigorously about latency, reliability, throughput, and cost in designing platform capabilities. Thrive in a fast-paced environment and enjoy balancing pragmatic engineering with long-term technical excellence. About OpenAI OpenAI is an AI research and deployment company d

About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a

About the Team The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. 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 The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. This role is based in San Francisco, CA. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees. 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 depl

About the Team Our Robotics team is focused on unlocking general-purpose robotics and advancing toward AGI-level intelligence in dynamic, real-world environments. Working across the full model and systems 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 physical constraints of real-world systems to improve people’s lives. About the Role We're looking for an experienced Electrical Engineer to help develop the next generation of robotic systems at OpenAI. This role spans the full lifecycle of hardware development, from early concept exploration and prototyping through circuit design, component selection, PCB layout, bring-up, integration, and deployment. Engineers in this role are expected to independently drive significant hardware efforts from initial concept through deployment. You will translate ambiguous goals into concrete engineering plans, make key technical decisions, coordinate closely with cross-functional partners, and own execution through the iterations required to deliver a successful system. Many of the systems we build are still being defined. You will work closely with mechanical, firmware, software, controls, and research teams to evaluate new ideas, develop novel hardware, and integrate it into robotic platforms. Success in this role requires strong engineering judgment, comfort operating in ambiguous spaces, and the ability to balance rapid experimentation with the discipline required to build reliable and scalable systems. The ideal candidate enjoys building things from first principles and is equally comfortable evaluating a new technology, debugging a prototype on the bench, reviewing PCB layout details, and driving system integration efforts. You should be able to move quickly when appropriate, but also know when investing in robustness, simplicity, or infrastructure will create leverage for future development. This role is

About the Team The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life. About the Role We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume. In this role, you will: Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory. Build proactive testing and scale validation pipelines for dataset loading at GPU scale. Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience. Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt. Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized. Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training). Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets. You might thrive in this role if you: Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure.

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 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

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 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 We are building general-purpose robotics. In the short term, we are focused on robots to support skilled workers to build our future infrastructure. In the long term, we imagine everyone having a personal robot doing anything they need. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research. About the Role As a Firmware Engineer, you will define and drive the architecture of embedded systems for next-generation hardware products. You will own foundational firmware decisions across real-time execution, device bring-up, hardware interfaces, fault handling, safety mechanisms, and production readiness. We’re looking for someone with deep experience building safety-critical or high-consequence systems, where failures can have meaningful consequences. You should be comfortable reasoning about risk, designing for diagnosability and graceful degradation, and creating engineering practices that raise the reliability bar for the entire team. You should also be unusually good at moving fast. Sometimes the right answer is a carefully reviewed architecture that will endure for years; sometimes it is getting a rough-but-useful prototype working by the end of the afternoon so the team can learn something concrete tomorrow. We value engineers who know the difference, make that call well, and can operate credibly in both modes. You will be both a technical leader and a hands-on builder: setting direction, reviewing critical designs, unblocking the hardest problems, and writing production firmware when it matters most. Our embedded stack uses a lot of Rust. Extensive experience in the language is a big help! This role is based in San Francisco, CA. This role will be expected to be in office 4 days per week and offer relocation assistance to new employees. In this role, you will: Rapidly bring up new hardware and set execution pace for the team. Lead firmware architecture for embedded systems spanning boot, RTOS/runtime behav

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 Codex Research 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 the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measu

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Learn more about OpenAI’s approach to safety. Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. About the Role At OpenAI, we're dedicated to advancing artificial intelligence, and we know that creating a secure and reliable platform is vital to our mission. That's why we're seeking a software engineer to help us build out our trust and safety capabilities. In this role, you'll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You'll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner. Your Responsibilities: Architect, build, and maintain anti-abuse and content moderation infrastructure designed to protect us and end users from unwanted behavior. Work closely with our other engineers and researchers to utilize both industry standard and novel AI techniques to measure, monitor and improve AI models’ alignment to human values. . Diagnose and remediate active incidents on the platform and build new tooling and infrastructure that address the root causes of system failure. You might thrive in this role if: You have built and run production services in a high growth, rapidly scaling environment. You can debug live issues and restore systems quickly. You have worked on content safety, fraud, or abuse, or are motivated and excited to work on present-day (“now-term”) AI safety. You have experience with Python or with modern languages such as C++, Rust, or Go, and are able to quickly ramp up on Py

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 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’re looking for a GPU Inference Engineer to contribute to improvements in model serving efficiency for our Robotics research. This is a high-impact role where you’ll drive initiatives to optimize inference performance and scalability. You’ll also be engaged in model design, to help assist our researchers in developing inference-friendly models. This role is critical to scaling the team’s broader goals - it will directly enable leadership to focus on higher-leverage initiatives by building a stronger technical foundation. In this role you will: Perform engineering efforts focused on improving model serving, inference performance, and system efficiency Drive optimizations from a kernel and data movement perspective to improve system throughput and reliability Partner closely with research and product teams to ensure our models perform effectively at scale Design, build, and improve critical serving infrastructure to support Robotics growth and reliability needs You might thrive in this role if you: Have deep expertise in model performance optimization, particularly at the inference layer Have a strong background in kernel-level systems, data movement, and low-level performance tuning Are excited about scaling high-performing AI systems that serve real-world, multimodal workloads Can navigate ambiguity, set technical direction, and drive complex initiatives to completion 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. About OpenAI OpenAI i