Quality Manager Jobs

About this Role OpenAI’s Finance organization is helping build the company and finance team of the future. Across Corporate Finance, Strategic Finance, Accounting, Tax, Treasury, Procurement, Real Estate & Workplace, Corporate Development, and Economic Research, teams are using OpenAI’s products to reshape core workflows, improve operating leverage, and surface practical lessons about how AI changes enterprise functions. As this work scales, Finance is becoming both a proving ground for real-world AI adoption and an increasingly important proof point for customers, and a feedback loop for Product, Research and Revenue teams. The opportunity is no longer just to capture isolated examples, but to turn them into a coherent program that strengthens OpenAI’s internal operations, informs product development, and helps the company explain what high-value enterprise AI adoption looks like in practice. The Visual Storytelling & AI Innovation Lead partners directly with the Chief of Staff to the CFO to turn Finance’s most important work into clear, visually compelling executive artifacts. This person will personally create CFO-facing presentations, board materials, executive briefings, customer-facing materials, and reusable design systems; shape the story architecture for high-stakes leadership and external moments; and establish the visual storytelling and presentation quality bar across Finance. The role will work closely with Global Affairs, Corporate Communications, Investor Relations, and Marketing to ensure this work supports broader messaging, audience, and channel strategies. The role will also turn Finance AI workflows into credible demos, proof points, and transformation stories; help Economic Research package and amplify its work; identify and elevate flagship use cases with Finance and Enterprise Platforms & Technology leaders; and develop content and materials that support customer and external engagement. This is a hands-on individual contributor ro

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 Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. 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 Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

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 Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in NYC. 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 Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript, or compar

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products, including next-generation ads experiences, that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers, advertisers, and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring new ad experiences into real-world systems across OpenAI surfaces at global scale, including thoughtfully integrating them into the core ChatGPT experience. About the Role We’re looking for an experienced Software Engineer to help build the creative rendering and presentation layer of OpenAI’s ads ecosystem. This is a foundational role responsible for defining how ads are structured, rendered, and delivered across different surfaces, platforms, and media types. You’ll work across the full technical stack to build infrastructure and tooling for new ad formats, including text, image, video, native, conversational, and interactive experiences. You will help ensure these formats render reliably, perform efficiently, and feel natural within the core ChatGPT experience. You’ll collaborate deeply with Product, Design, and Research to create ads experiences that are useful, high-quality, privacy-preserving, and aligned with OpenAI’s standards for safety and user trust. In this role, you will: Design, build, and

About the Team The OpenAI 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 As a Senior Software Engineer, ML Systems & Training Infrastructure, you will be a deeply hands-on engineering force multiplier for the robotics team. You will help keep the training framework and surrounding infrastructure healthy, review and improve code quickly, debug failures across ML systems and infrastructure, and unblock researchers and engineers when the path from idea to working training job gets rough. We’re looking for people who love writing, reading, reviewing, and fixing code; who can get productive quickly in unfamiliar systems; and who bring strong practical judgment without a lot of ego or process overhead. This role will be based in San Francisco, CA and be expected in office 5 days per week and offer relocation assistance to new employees. In this role, you will: Review, improve, and clean up code across training frameworks and adjacent infrastructure. Identify risky or low-quality changes before they land, and raise the code quality bar without slowing the team down. Debug issues across ML training systems, GPUs, clusters, networking, and related infrastructure. Help researchers and engineers unblock broken training jobs, flaky workflows, and brittle internal tooling. Improve the reliability, maintainability, and usability of the robotics team’s training framework. Move quickly on practical engineering problems that directly affect team velocity. You might thrive in this role if you: Have strong software engineering fundamentals and excellent code review judgment. Have experience with ML systems, training fr

About the Team Safety Systems works to ensure OpenAI’s most capable models can be developed and deployed responsibly. Our work spans evaluations, safeguards, red teaming, deployment decisions, and the systems that help OpenAI understand and reduce risk as models become more capable and widely used. Within Safety Systems, the Trustworthy AI team is growing its safety transparency function: a practice focused on helping external audiences understand OpenAI’s technical safety work with greater clarity, rigor, and continuity. We create and improve the public artifacts that explain how our systems are evaluated for safety, what safeguards we build, what decisions we make, and where uncertainty remains. This work includes system cards, the Deployment Safety Hub, safety-related blogs, public governance documents, and other outputs that communicate technical safety topics to external audiences. It also includes building new ways to make technical safety information easier to understand, navigate, and use—including AI-assisted workflows, data visualizations, and interactive tools that make complex technical work more legible over time. About the Role We are looking for a Safety Transparency Editor to own the editorial quality of key safety transparency artifacts and systems. This is a hands-on role for someone who can write crystal-clear, pitch-perfect explanations of the hardest and highest-stakes technical safety topics that OpenAI tackles, and who can lean into AI to build systems that help the broader organization do this work better. Your core responsibility is to shape and execute how our technical safety work is externally communicated: identifying the narrative thread, exercising judgment about which details matter, determining where additional context, explanation, or supporting evidence is needed, translating complexity without sacrificing precision, and helping external audiences understand both the safety measures we’ve taken and the uncertainties that remain. To

About the Team Codex is OpenAI’s first-party developer product focused on agentic software engineering. We’re building tools that help engineers design, write, test, and ship code faster—safely and at scale. We partner tightly with research and product to translate model advances into tangible developer productivity. About the Role As a Data Scientist on Codex, you will measure and accelerate product-market fit for AI developer tools. You’ll define what “developer productivity” means for our product, run experiments on new coding models and UX, and pinpoint where the model helps or hurts across languages and tasks. Your insights will directly shape how an entire industry builds software. 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 Embed with the Codex product team to discover opportunities that improve developer outcomes and growth Design and interpret A/B tests and staged rollouts of new coding models and product features Define and operationalize metrics such as suggestion acceptance, edit distance, compile/test pass rates, task completion, latency, and session productivity Build dashboards and analyses that help the team self-serve answers to product questions (by language, framework, repo size, task type) Diagnose failure modes and partner with Research on targeted improvements (model quality signals, user feedback, evals) You might thrive in this role if you have 5+ years in a quantitative role at a developer-facing or high-growth product Fluency in SQL and Python; comfort with experiment design and causal inference Experience defining product metrics tied to user value Ability to communicate clearly with PM, Eng, and Design—and to influence product direction You could be an especially great fit if you have Strong programming background; ability to prototype, run simulations, and reason about code quality Familiarity with IDE/extensi

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 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 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 seeking talented Robotics Software Engineers to expand our robotics data collection and evaluation program. This highly technical role involves designing, implementing, and optimizing software solutions across diverse robotics hardware. You'll work closely and collaboratively with multidisciplinary teams; including software, hardware, research, and operations - to drive advancements in our robotic systems. This role is based in San Francisco, CA, and requires in-person 4 days a week. In this role, you will: Help develop and grow our data collection labs, owning the entire integration lifecycle, from identifying and sourcing new hardware to collaborating with mechanical and electrical engineers on setup, software integration, and operational deployment. Develop innovative robot control interfaces suited to a variety of morphologies, environments, and tasks. Collaborate closely with research and engineering teams to develop automation tools and machinery that facilitate the evaluation of advanced robotic policies. Lead the design and implementation of data collection, visualization, and quality control processes. You might thrive in this role if you: Have 5+ years of professional software engineering experience developing and shipping production-quality systems in robotics or hardware-integrated environments. Have extensive experience integrating and deploying industrial automation systems, off-the-shelf robotics platforms, or custom hardware into production environments. Bring hands-on experience delivering production-quality software

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 Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in Tokyo. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Travel is expected in this role, mainly within Japan. To succeed in this position you must be bilingual—fluent in both Japanese and English (spoken and written). Please note that your resume must be submitted in English, and the interview process will include conversations in both languages. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bri

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We’re looking for a product manufacturing engineer, who will be responsible for driving technical initiatives related to manufacturing to ensure product success from concept to launch and through mass production with a specific focus on PCB and PCBa manufacturing and process. You’ll have the opportunity to work with a wide range of stakeholders, from design engineering and operations teams,TPMs, external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. 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: In this role, you’ll be responsible for driving manufacturing and quality initiatives to ensure product success from concept to launch Lead the product design and the manufacturing process for next-gen AI hardware system development, you will have the opportunity to work with a wide range of stakeholders, from design engineering and operations teams, TPMs and external industry vendors and partners to ensure that all products are developed and delivered on time and to the highest quality standards. Lead the team to establish NPI product manufacturing process, systems and quality controls, defining clear milestones and deliverables, drive internal process improvements across multiple terms and functions Provide hands-on product manufacturing analysis during desi

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 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