Software Engineer, Codex Core Agents

About the Team The Codex Core Agent team builds the kernel of Codex. We own making the agent better, accelerating research, and making those improvements real in production for our users. That means working across the systems that make Codex actually function as an agent in the real world: the production performance envelope around tokens, latency, reliability, cost, and capacity; the core execution loop and interfaces that turn models into useful behavior; the shared infrastructure that enables other teams to build on Codex; and the feedback loops that turn real-world usage into better models and better agent behavior over time. About the Role We’re looking for engineers to build the infrastructure that powers Codex agents in production. This role focuses on the systems that let models safely execute code, interact with tools, complete long-running tasks, and operate reliably and efficiently at scale. You’ll design and operate the infrastructure behind sandboxed execution, orchestration, stateful workflows, app-server and SDK boundaries, and model rollouts. You’ll work at the intersection of distributed systems, developer tooling, and AI, building primitives that make Codex faster, safer, more reliable, and easier for the rest of the organization to build on. What You’ll Do - Design and build execution environments for AI agents, including sandboxing, isolation, and reproducibility. - Develop systems for agent orchestration across multi-step, tool-using workflows. - Build infrastructure for running, testing, and debugging code generated by models. - Create state and memory systems that allow agents to persist context across long-running tasks. - Optimize tokens, latency, reliability, and cost across Codex’s production fleet. - Support model rollouts, capacity planning, and the core tradeoffs between quality, speed, and economics to manage a fleet of frontier agents at scale. - Build shared platform capabilities that unblock product teams, partner teams, and open source Codex. You Might Be a Good Fit If You - Have strong experience in distributed systems or infrastructure engineering. - Have built systems involving containers, sandboxing, or virtualization. - Are comfortable working across backend systems, APIs, and developer tooling. - Care deeply about system reliability, performance, and security. - Enjoy working on ambiguous, zero-to-one problems. - Want to help build the systems that turn model capability into a dependable software engineering agent. Bonus Points - Experience with code execution platforms, CI/CD systems, or build systems. - Experience coding in Rust - Familiarity with LLMs, agents, or tool-use frameworks. - Background in security engineering or isolation systems. - Experience building developer platforms, IDE tooling, or open source infrastructure. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance

Have strong experience in distributed systems or infrastructure engineering. Have built systems involving containers, sandboxing, or virtualization. Are comfortable working across backend systems, APIs, and developer tooling. Care deeply about system reliability, performance, and security. Enjoy working on ambiguous, zero-to-one problems. Want to help build the systems that turn model capability into a dependable software engineering agent. Bonus Points: Experience with code execution platforms, CI/CD systems, or build systems. Familiarity with LLMs, agents, or tool-use frameworks. Background in security engineering or isolation systems. Experience building developer platforms, IDE tooling, or open source infrastructure.

Design and build execution environments for AI agents, including sandboxing, isolation, and reproducibility. Develop systems for agent orchestration across multi-step, tool-using workflows. Build infrastructure for running, testing, and debugging code generated by models. Create state and memory systems that allow agents to persist context across long-running tasks. Optimize tokens, latency, reliability, and cost across Codex’s production fleet. Support model rollouts, capacity planning, and the core tradeoffs between quality, speed, and economics to manage a fleet of frontier agents at scale. Build shared platform capabilities that unblock product teams, partner teams, and open source Codex.