Quality Specialist Jobs

About the Team The Cybersecurity Products team builds products at the frontier of AI and cybersecurity. Our work includes Codex Security and related cyber products that turn advances in model capability into dependable tools for defenders. We help teams find, validate, and remediate vulnerabilities, continuously improve the security of software, and test AI-powered applications before they reach production. About the Role As a Full Stack Software Engineer, you will build the product experiences and systems that make AI-powered security useful in real engineering environments. You will work across web surfaces, APIs, orchestration, data models, and integrations to help security and engineering teams move from a codebase or application to evidence-backed findings, prioritized remediation, and revalidation. You will collaborate closely with product engineers, security researchers, and customer-facing teams. The work spans fast-moving product development and hard systems problems: long-running workflows, large repositories, sensitive data, reliability, observability, and a high bar for earning user trust. 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 end-to-end workflows for vulnerability discovery, security scanning, red teaming, findings review, remediation, and reruns. Design and operate backend services for long-running security work, including APIs, asynchronous orchestration, durable state, and integrations with developer workflows. Make complex security results actionable through clear product surfaces, strong evidence, thoughtful prioritization, and reliable reporting. Partner with security researchers, product teams, and users to evaluate quality, reduce noise, improve coverage, and ship safely. You might thrive in this role if you: Have experience shipping production full-stack products across modern web frontends and backend s

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role Forward Deployed Engineers lead complex deployments of frontier models in production. You will embed with customers where model performance matters, delivery is urgent, and ambiguity is the default. You will use this to map their problems,You will use this to map their problems, structure delivery, and ship fast. You will scope, sequence, and build full-stack solutions that create measurable value. You will also drive clarity across internal and external teams. You will identify reusable patterns and share field signal that influences the roadmap. Success in this role means owning the delivery state across workstreams. You will hold the bar on quality and pace and help OpenAI learn through execution. This role is based in Abu Dhabi. 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 c

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Enterprise Platform team builds the systems that help our GTM teams bring OpenAI products to customers at scale. This role sits close to our emerging ads business, partnering with Ads Sales, Operations, Product, Finance, Legal, and Engineering to create reliable workflows for advertiser lifecycle, campaign readiness, approvals, and revenue operations. About the role Our GTM team helps customers understand the transformational potential of OpenAI’s models, and our internal systems should make that work faster, cleaner, and more intelligent. We’re looking for a Salesforce Ads Systems Engineer to design and build the Salesforce foundation for our ads business. You’ll partner with Ads Sales, Ads Operations, Product, Finance, Legal, and data teams to turn complex advertiser and campaign workflows into scalable, auditable systems. This is an execution-heavy, builder role. The primary charter of this role is ads GTM systems: advertiser account and opportunity workflows, campaign/order readiness, approvals, integrations, and automation that keep ads motions moving cleanly from pipeline through launch, billing, measurement, and reporting. In this role, you'll: Build Salesforce solutions for ads GTM : Develop user experiences, objects, automations, and guardrails that help Ads Sales and Operations manage advertisers, opportunities, insertion orders, campaign readiness, approvals, and launch handoffs with high data quality. Engineer integrations across the ads stack : Connect Salesforce with ads platforms, product catalogs, pricing/rate-card systems, data warehouses, billing tools, measurement workflows, CLM, and e-signature systems so advertiser and campaign data stays accurate and audit

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 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 Supply Chain Program Manager, you will own material readiness and supply chain execution for critical hardware programs spanning custom silicon, systems, memory, storage, networking, and rack infrastructure. You will work cross-functionally with Engineering, Strategic Sourcing, Manufacturing Operations, Finance, Planning, Quality, and external suppliers to develop and execute scalable supply strategies that support aggressive product development and deployment timelines. This role requires deep understanding of hardware supply chains, material planning, NPI execution, supplier management, and operational scaling in constrained and rapidly evolving environments. In this role you will: Material Readiness & Supply Planning - Own end-to-end material readiness across NPI and production phases, including building the necessary framework and processes for enablement. Drive supply planning and execution for long lead-time and constrained commodities including ASICs, HBM, DDR, SSDs, networking, optics, power, thermal, and mechanicals. Build and manage material readiness plans aligned to proto/pre-EVT, EVT, DVT, PVT, and mass production schedules. Monitor supply health, lead times, inventory positions, allocation risk, and capacity constraints. Drive shortage management, allocation mitigation, and recovery planning. Coordinate supply commits, forecast alignment, and supply continuity planning with suppliers and manufacturing partners. Cross-Functional Program Ma

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 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 As a foundational FDE manager, you’ll lead FDE through high-stakes, ambiguous customer deployments and own technical and business value outcomes end to end. You’ll grow a team that can operate under pressure and help OpenAI learn from the field. You’ll partner closely with Product, Research, Sales, and GTM to ensure fieldwork informs roadmap priorities, drives new exploration, and supports safe deployment at scale. Your decisions will influence how OpenAI is trusted by the customers closest to our deployment work. Your success will be measured by how consistently your team ships, how clearly you deliver signal to Research and Product, and how durable your team and delivery model prove to be. This role is based in New York City We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. This role also will require travel up to 25%. In this role you will Lead and grow a team of FDE delivering production systems with frontier models Own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality Codify what works into tools, playbooks, and roadmap inputs that create leverage for both OpenAI and our wider developer community Notice early indicators and raise them with urgency, whether in product behavior, customer environments, or delivery practices Use judgement to distinguish what requires action and what does not Set a high bar for FDE performance and support each person’s growth through direct, actionable feedback Define how we staff and support field teams that can scale without added complexity You might thrive in this role if you Bring 8+ years of engineering or technical delivery experience, including 2+ years managing high-performing FDE or custo

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 OpenAI’s Enterprise Go-To-Market organization helps the world’s largest companies adopt and scale our AI platform across their business—from ChatGPT Enterprise to our developer platform and APIs. We partner with organizations across Financial Services, Life Sciences, Retail, Manufacturing, Technology, and other key industries across Asia Pacific to build AI-powered customer experiences, transform operations, and accelerate innovation. As adoption accelerates through pilots, experimentation, and developer-led use cases, the GTM team turns that momentum into durable, enterprise-wide deployments. Sales Development sits at the front of this motion—where technical curiosity becomes executive engagement and OpenAI’s enterprise relationships begin. About the role We are hiring a APAC Sales Development Leader to build and lead OpenAI’s enterprise Sales Development organization across Asia Pacific. Reporting directly to the Head of Global Sales Development, this role is a core part of the Enterprise GTM leadership team. This is a high-impact leadership role focused on scaling pipeline generation and market development across a diverse and rapidly growing region. You will define how OpenAI engages enterprise customers across APAC, build regional SDR leadership and teams, and create the operating model that converts product interest, developer activity, and inbound demand into high-quality pipeline for our Enterprise and Strategic Accounts organizations. In this role, you will Build and scale OpenAI’s APAC Sales Development organization, including hiring strategy, org design, enablement, and performance management. Lead and develop front-line SDR managers and SDR teams across key APAC markets. Own the regional enterprise pipeline generation strategy, ensuring consistent, high-quality opportunity creation across the region. Translate product usage, pilots, developer engagement, and inbound interest into qualified enterprise opportunities. Develop localized and ve

About the Team OpenAI's Research Data Team exists to accelerate the evaluation, safety and capabilities of our models and products. Made up of technical operators and software engineers, we design the methods in which we acquire and create data. About the Role As a Research Program Manager (RPM), Data Acquisition, you will partner with research, engineering, and operations to design and implement pragmatic solutions for acquiring data. You will be a key interface between our research roadmap and external data offerings. This role is based in our San Francisco HQ and will be part of a team of RPMs pushing the frontier of data acquisition. In this role, you will: Partner deeply with research: Work with researchers to scope data needs, define success criteria, and translate priorities into clear execution plans. Shape the data acquisition pipeline: Identify, evaluate, and advance high impact data opportunities - balancing research value, feasibility, quality, and responsible execution. Unblock yourself: Move work forward even when the path is unclear — using technical judgement, creative problem solving, and scrappy execution to make progress while longer-term solutions are still forming. Build lightweight systems and visibility: Use SQL, Python, dashboards, and simple tooling to track performance, quality, and blockers. Drive technical roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. Scale your impact: Equip vendors and internal teams with the context, standards, and operating rhythms needed to focus on the most important problems. You’ll thrive in this role if you: Are proficient in SQL and Python for analysing datasets, querying databases, building dashboards, and generating actionable insights. Are comfortable using APIs, automation, and AI tools such as Codex to accelerate workflows, remove manual overhead, and upskill quickly in unfamiliar technical areas.Experience sou

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 Frontier Systems Foundations, part of Compute Foundations at OpenAI, builds the systems software foundation that turns new compute infrastructure into reliable, usable capacity for frontier model training. Our mission is to make some of the world's largest GPU clusters work reliably for frontier training. We bring new platforms and clusters online, safely maintain installed fleets, and partner with hardware, infrastructure, and research teams to resolve the system-level issues that keep jobs from running. That means building and maintaining the software closest to the machine: Linux and Ubuntu operating-system images, kernels and modules, drivers, packages and repositories, disks and boot configuration, firmware integration, provisioning, and system-level validation. We make these components reproducible, compatible, and safe to operate across heterogeneous fleets. About the Role We are looking for systems software engineers with deep Linux and host-systems experience to build, qualify, and maintain the operating-system foundation for OpenAI's frontier compute fleet. Relevant backgrounds include kernel and module development, Linux distribution or image engineering, package management, firmware and driver integration, disks and boot, and bare-metal provisioning. You'll work closely with hardware engineers, vendors, and infrastructure teams to bring up new platforms, integrate system components, and debug failures across firmware, disks, boot, operating systems, kernels, drivers, and workload interactions. Your work will directly influence how quickly new capacity becomes usable and how reliably large GPU fleets operate. You should be comfortable writing and maintaining production-quality systems software and automation, but we do not expect expertise across every layer. This is an opportunity to go deep on challenging systems problems while building the image, package, qualification, and recovery paths that power the next generation of frontier models