Codex Deployment Engineer in United States

About the Team The Statsig team is responsible for the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Teams across ChatGPT, Codex, model measurement, monetization, business subscriptions, developer products, and shared infrastructure rely on Statsig to introduce capabilities safely, measure their impact, and make high-confidence product decisions. About the Role As a Product Lead on the Statsig team, you will define how experimentation, rollout, configuration, and analytics become a simple, reliable, and trusted part of how every OpenAI product team ships. You will set strategy across multiple product and platform workstreams, translate company-wide needs into durable capabilities, and help Statsig become a core part of OpenAI’s product development system. We’re looking for a product leader who combines strong product judgment, technical fluency, and deep analytical thinking. You should be comfortable navigating ambiguous customer needs, influencing teams across the company, and balancing rapid adoption with reliability, usability, and measurement quality. 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. Travel requirements should be confirmed with the recruiter before publishing. In this role, you will: Define the product vision, strategy, and roadmap for experimentation, feature management, dynamic configuration, rollout safety, and analytics. Partner with product, engineering, research, data, design, and infrastructure leaders to turn recurring launch and measurement needs into reusable platform capabilities. Develop a deep understanding of workflows across ChatGPT, Codex, model measurement, monetization, subscriptions, and developer products, then establish clear priorities across competing needs. Drive adoption by making sophisticated experimentation and analytics c

About the Team OpenAI’s mission is to ensure that artificial general intelligence benefits all of humanity. Our product teams work across research, engineering, product, data, and design to bring OpenAI’s technology to people and businesses around the world. Design plays a critical role in making powerful AI intuitive, useful, and trustworthy. We hold a high bar for quality and build experiences that earn users’ confidence, while moving quickly and learning from real-world feedback. We favor early validation and continuous refinement over waiting until every detail is perfect. About the Role We’re looking for a Product Design Leader to shape how startups, small businesses, and growing teams discover, adopt, and unlock lasting value from Codex and ChatGPT. You’ll lead design across the B2B growth journey, creating experiences that turn the potential of AI into meaningful, everyday impact for this user base. This role is a mix of team leadership and hands-on design execution. You’ll lead and develop a small team of designers, contribute directly to high-impact projects, and help set the standard for impactful, simple, user-centric experiences. You balance exceptional craft with momentum, creating a culture where the team launches, learns, and improves quickly. You already use tools such as Codex to extend what you can build. As a leader, you help designers strengthen their judgment, confidence, and influence through clear and actionable feedback. You’re also a highly effective cross-functional partner who brings people together, navigates ambiguity, and builds alignment through clear communication and collaborative problem-solving. Codex is on an extraordinary trajectory, and this role offers a rare opportunity to work across both sides of the product: the consumer experiences through which people first discover and adopt our technology, and the business experiences that help teams use it together. You’ll bring a high bar for craft, strong product judgment, and comfor

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. As a Staff Product Manager, AI Foundations at Vanta, you will build the core AI capabilities that power Vanta’s AI product experiences: the agent harness our agents are built on, and the quality and evaluation stack that makes them trustworthy. The AI pillar is making Vanta the intelligence layer for security and compliance work, wherever that work starts. We build the AI products and foundations that work across Vanta: a cohesive first-party Vanta Agent experience, headless surfaces like MCP and CLI that bring Vanta into tools like Claude Code and Codex, and the shared capabilities that let every team ship high-trust AI products. This role sits behind Vanta’s customer-facing AI experiences. Today, every team shipping AI features has to answer the same hard questions on their own: how to define quality, how to evaluate it, and how to know a change is safe to ship. You will turn those answers into shared foundations, so the AI experiences our customers rely on get better and more trustworthy over time. What you’ll do as a Staff Product Manager, AI Foundations at Vanta: Own the strategy and roadmap for Vanta’s core AI capabilities: the agent harness and the AI quality and evaluation stack Live in agent traces to build intuition for how customers actually use our AI products, and turn that into the highest-leverage improvements Make Vanta’s AI products win on quality: build golden datasets, automated evaluators aligned to expert judgment, and self-serve tooling so PMs, subject-matter experts, and designers can run evals without an engineer in the loop Scale the agent harness: shape the core capabilities Vanta’s agents are built on

At Vanta, our mission is to help businesses earn and prove trust. We believe that security should be monitored and verified continuously, and we empower companies to practice better security and prove it with ease. Vanta has a kind and talented team, and while some have prior security experience, many have been successful at Vanta without it. Customers increasingly use AI agents like Claude Code, Codex, Cursor, and internal Slack agents to run their business processes, and security and compliance work is no exception. For those agents to do that work, they need access to Vanta’s trust graph and intelligence layer. Vanta is building for that world: security and compliance products that customers can use through Vanta, through third-party agent platforms, and inside their own internal tools. As Senior Product Manager, Agent Ecosystem, you will own Vanta’s external agent surfaces: MCP, CLI, and plugins in marketplaces like Claude Code, Codex, and ChatGPT. Your job is to make Vanta the trusted compliance layer that agents rely on. You will define the strategy, ship the products, and own the outcomes. What you’ll do as a Senior Product Manager, Agent Ecosystem at Vanta: Own the strategy and roadmap for Vanta’s agent ecosystem products. Define how agents discover, access, and safely use Vanta capabilities, partnering with the platform teams that own APIs and authentication. Hold outcome parity as a product principle: work a customer can complete in Vanta should be possible through MCP, CLI, and plugin surfaces too. Lead marketplace and plugin launches, aligning product, engineering, legal, security, and go-to-market around each one. Partner with engineering and design to ship secure, reliable developer products. Build the developer-facing marketing motion: external agent documentation and customer stories that show what MCP and CLI users have unlocked. Partner with the product partnerships and alliances team on co-marketing with agent platforms like Anthropic and OpenAI,

About the Team The Product Policy team is responsible for the development, implementation, enforcement, and communication of the policies that govern use of OpenAI’s services, including ChatGPT, GPTs, the GPT Store, Codex, and the OpenAI API. About the Role We are looking for a Research and Advisory Partnerships Lead to build and manage the relationships, partnerships, and advisory structures that bring independent external expertise into our product and policy decisions. 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 identify and engage researchers, civil society organizations, subject-matter experts, and other external stakeholders whose perspectives can strengthen how we develop and deploy AI. You will establish and manage advisory councils, develop research partnerships with the academic community, and work closely with internal teams to translate external insights into actionable guidance. This role sits at the intersection of product, policy, research, and governance. It is well suited to someone who is comfortable building relationships across disciplines and designing processes that ensure outside expertise meaningfully informs internal decision-making. This role can be based in San Francisco or New York City. 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: Develop, launch, and manage external advisory councils and other governance mechanisms that provide structured input on product and product policy. Build and maintain relationships with external experts, researchers, civil society organizations, and other stakeholders who can inform high-priority product and product policy decisions. Identify when external consultation can improve internal decision-making, and develop engagement strategies tailored to specific products, policy questions, and emer

About the Team OpenAI’s Governance, Risk, and Compliance team helps ensure security and privacy are grounded in how our products and systems actually operate. Assurance Operations partners with Security, Engineering, Infrastructure, Product, Privacy, and Legal to make controls provable, risk decisions explicit, and audit readiness a result of well-designed systems. About the Role We are hiring a technical, product-minded GRC builder who can own consequential audits while improving the control and evidence systems behind them. You will build a reusable common control framework, use Codex to automate assurance work, validate changing system scope, and turn repeated audit friction into measurable improvements. We are looking for someone who questions inherited assumptions, solves novel problems creatively, works closely with engineers, and makes the next audit easier by improving the underlying system. You’ll be responsible for: Lead external, internal, customer, and certification audit work from scoping through evidence review, fieldwork, remediation, and closeout. Build a common control framework linking risk, control intent, implementation, owner, system, environment, evidence, and applicable frameworks. Validate actual scope and ownership instead of assuming last year's controls, product boundaries, or evidence remain accurate. Use Codex to build and test evidence checks, control mappings, request triage, owner workflows, monitoring, and remediation reporting. Partner with engineers on cloud architecture, identity, logging, data flows, software changes, vulnerabilities, and control effectiveness. Design maintainable, permission-aware tools that preserve source provenance, human review, and evidence integrity. Reduce repeated requests and operational burden for control owners through measurable workflow improvements. Define roadmaps, decision rights, milestones, success metrics, and clear cross-functional escalations. We’re looking for someone with: Direct ownership

About the role We are building a higher education researcher motion that helps funded labs adopt OpenAI across core research workflows. This role will develop relationships with principal investigators, researchers, research software engineers, research computing teams, and university technology leaders, then translate high-value use cases into sustained Pro, Codex, API, and ChatGPT Edu usage. This is a hybrid business development and program management role. You will identify and qualify priority labs, design phased access and fellows programs, run pilots, remove technical and institutional blockers, and create repeatable paths from individual researchers to lab- and institution-level adoption. Additionally, this role will launch and manage a community of researchers with events, communications and support. In this role, you will: Build a pipeline of funded labs, research centers, and technical champions at priority R1 universities; qualify opportunities based on workflow value, funding path, influence, and expansion potential. Run discovery with researchers and university stakeholders to understand workflows, data and security needs, procurement constraints, and success criteria. Design and operate phased access and fellows programs, including eligibility, selection, offer mechanics, onboarding, office hours, community programming, and pilot goals. Translate research workflows into effective use of Pro, Codex, API, and ChatGPT Edu in partnership with Solutions, Product, and Education account teams. Manage pilots end to end, remove trust, funding, and technical blockers, and drive measurable activation, retention, and expansion. Turn early usage into product feedback, workflow documentation, peer proof, case studies, and repeatable enablement. Build clear handoffs and expansion paths from researcher to lab to institution; track fellow selection, activation, retained usage, workflow proof, conversion, and expansion. You might thrive in this role if you: Relevant exp

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After joining OpenAI, the team began its next chapter: bringing deep product expertise, customer intuition, and mature platform infrastructure into the product development system used by every OpenAI team. Today, teams across ChatGPT, Codex, model measurement, consumer monetization, business subscriptions, developer products, and shared infrastructure rely on Statsig to safely introduce new capabilities, measure impact, and roll changes forward or back with confidence. We are at a defining moment as adoption accelerates and the platform becomes a company-wide standard. About the Role We are looking for an Engineering Manager, Statsig Product to lead the product engineering organization responsible for Statsig’s post-acquisition journey at OpenAI. You will define how experimentation, rollout, configuration, and analytics become a simple, reliable, and trusted part of how every OpenAI product team ships. You will set strategy across multiple product and platform workstreams, build the organization and leadership structure needed for the next phase, and establish the operating model for a platform that serves teams across the company. The right leader can operate across product strategy, technical architecture, organizational design, developer experience, reliability, and executive alignment. You will help preserve what made Statsig strong while integrating it deeply into how OpenAI launches, measures, learns, and makes product decisions. In this role, you will: Build, lead,

About the Team The Cloud Agents team builds product infrastructure for long-running agents in the cloud: orchestration, sandboxing and isolation, secure environment connectivity, secrets and identity, observability, reliability, and cost controls. These agents securely connect to diverse developer and customer environments and use tools to accomplish goals. We partner closely with product, research, and infrastructure teams to turn agentic capabilities into dependable platforms for OpenAI products and developers building on OpenAI. About the Role We are looking for an experienced software engineer to help build and scale our cloud agent platform. You will design and operate systems for orchestrating agents at scale. You will work closely with product engineers on ChatGPT, API, and Codex to define the right abstractions and enable them to ship products quickly. Strong backend or infrastructure experience is important; experience with Python, Rust, distributed systems, cloud infrastructure, or product platforms is especially helpful. In this role, you will: Design and scale the orchestration, sandboxing and storage systems that run agentic workloads for Codex, ChatGPT, and the OpenAI API. Partner with product engineers to build a platform that enables them to ship quickly and turn feedback into robust abstractions. Improve reliability, security, performance, and cost efficiency for long-running agents. Deploy services that can operate across different environments and clouds. Your background might look something like: 9+ years of professional engineering experience, excluding internships, in relevant roles at technology and product-driven companies. Experience leading large-scale backend, platform, or infrastructure projects from ambiguous problem statements to production systems. Proficiency in one or more backend languages such as Python, Go, Rust, TypeScript, or similar, and the ability to move across service, platform, and product boundaries. Strong understanding

About the team The Computer Use and New Interfaces team is focused on discovering and building the next generation of AI-native interfaces. We believe that the value of AI is increasingly constrained not by model capabilities, but by the ways people interact with those capabilities. Our mission is to create new interaction paradigms that unlock the full potential of AI and integrate it more deeply into people's lives and work. Our team does both near-term product development and longer-term product incubation that can influence experiences across ChatGPT, Codex, future OpenAI products, and emerging device platforms. We work in a highly collaborative, design-driven environment where engineering, product, and design operate as one team. We value rapid experimentation, prototyping, and iteration, creating the shortest possible path between an idea, a working system, and a product decision. About the role We're looking for exceptional engineers who are excited to invent entirely new ways for people to interact with AI. You'll work at the intersection of engineering, product, and design to explore, prototype, and build novel interface concepts that push beyond traditional software paradigms. This role requires comfort with ambiguity, strong product instincts, and a willingness to move fluidly between experimentation and production systems. You'll help shape both the capabilities and the user experiences that define how people engage with AI. In this role you will: Design, prototype, and build novel AI-native interfaces and interaction models. Develop foundational technologies and frameworks that enable generative UI and computer use experiences. Collaborate closely with designers, product thinkers, and engineers to rapidly explore and validate new concepts. Build end-to-end prototypes and production systems that can influence future OpenAI products. Contribute to platform technologies that can be adopted across multiple product surfaces. Help establish technical directio

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including AWS-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will Partner with strategic customers and in

About the team OpenAI’s Education team is building products and experiences that help learners, educators, and institutions benefit from AI in ways that are rigorous, useful, and grounded in real learning outcomes. The work spans both consumer and B2B education, with close collaboration across engineering, learning science, design, data, and research. This team sits in a highly strategic investment area for OpenAI, with strong opportunities to shape how product ideas flow across consumer and institution-facing experiences. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the role We’re looking for a product-minded Full Stack Engineer to help build OpenAI’s education products from the ground up. You’ll own end-to-end development across the stack, from early concepting and prototyping through production launch and iteration. This is an opportunity to work on a highly strategic, early-stage product area where engineering judgment, product sense, and customer empathy all matter. You’ll partner closely with leaders across the education org, including learning scientists, researchers, designers, and cross-functional partners, to turn emerging ideas into durable product experiences for schools, universities, and other education stakeholders. In this role, you will: Build and ship product experiences across the full stack for OpenAI’s education offerings Own projects end-to-end, from ideation and technical design through implementation, launch, and iteration Work closely with learning scientists and researchers to translate learning goals and evidence into product decisions Collaborate with design, data, and cross-functional partners to build thoughtful, high-quality user experiences Help define the engineering foundation for a growing education pod, including patterns, systems, and technical

About the Team The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After Statsig joined OpenAI, the team began the next chapter: bringing that deep product expertise, customer intuition, and mature platform infrastructure into OpenAI as the experimentation and rollout platform for every product we ship. Today, we support teams across ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and the shared infrastructure that connects them. These teams rely on Statsig to safely introduce new capabilities, compare product and model behavior, measure impact, and roll changes forward or back with confidence. We are at a defining moment in the platform journey. OpenAI has the data, product surface area, and pace of innovation to learn faster than almost any organization in the world, but that potential only becomes real if teams can experiment responsibly, measure clearly, and roll out changes safely. Adoption of the platform is accelerating rapidly across the company, and recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency for important services. Based out of OpenAI’s Bellevue office, we are a close-knit team that values in-person collaboration, urgency, craft, and impact. We build for other builders, and the best version of this team is one where every OpenAI product team can move faster because the experimentation and rollout layer is dependable, fast, and easy to use. About the Role We are l

We're building the platform that lets long-running autonomous agents operate safely inside NVIDIA's enterprise. These are not assistants on a developer's laptop. They are fleets of agents deployed in the cloud, running continuously at scale on shared accelerated compute. They take on real work across enterprise systems, so people get far more done than they could before. This role defines the constructs that agents are built from: the blueprints they start from, the tools, skills, and plugins that power them against enterprise data, the runtime safety harness that keeps them in bounds, and the connections into credential management, sandbox, memory, and observability. The team designs and ships these building blocks so that agent developers across the company can stand up a new agent, wire it in, and run it for days or weeks. Security and safe execution come out of the box, not something each team has to get right on its own. Today an agent runs inside a single harness. Claude, Codex, and open-source agent harnesses each work differently underneath, with their own execution model, tool interface, and telemetry shape. The platform smooths over those differences, so a single skill, safety policy, or trace works the same no matter which harness is running. We want to enable agents that act on a person's behalf, governed and secure, continuously evaluated and self-improving. These agents coordinate and hand work off to each other, with identity and policy following every hop. They route and tune themselves across harnesses from live eval signals, and get better from their own production telemetry instead of waiting on a human to retrain them. Have you run agents on a harness like Claude or Codex and hit the walls that show up when they run for real, for days, against live systems — and wanted them to learn from it on their own? We're building the platform that solves those problems once, for every team. What you'll b