The posting, in OpenAI's own words
archived Sep 11, 2026About the Team
OpenAI’s Applied AI Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. For software engineering organizations, this means helping customers adopt Codex and other OpenAI capabilities across the software development lifecycle—transforming how teams plan, build, test, review, and deliver software. We work directly with engineering leaders and hands-on developers to identify high-value opportunities, design and implement AI-powered development workflows, and scale what works across engineering organizations. We turn lessons from these deployments into better products, reusable architectures, and technical patterns that help developers everywhere get more value from Codex.
About the Role
As an Applied AI Engineer focused on Codex, you will partner directly with leading engineering organizations to design, build, and deploy AI systems that transform how software is developed. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from workflow and use-case selection through prototyping, evaluation, production rollout, and scaled adoption. You will work alongside engineering teams to build advanced AI coding workflows, integrations, automations, and evaluation systems—often using Codex itself as part of your development process. You will help customers make technical decisions involving model behavior, agentic workflows, developer environments, security, reliability, evaluation, and operational readiness, while ensuring deployments translate into measurable improvements in engineering productivity and software delivery. You will work closely with OpenAI Product, Research, Engineering, Security, Sales, and the broader Codex organization, translating real-world deployment experience into high-signal product and model feedback. Success is measured by production systems, sustained developer adoption, and meaningful improvements to how engineering organizations build software—not simply successful demonstrations or enablement activity. This role is based in our London office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
Read the full posting ↓
In this role, you will:
Partner directly with engineering leaders and hands-on developers to identify high-value opportunities for Codex and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. Design, build, and deploy AI-powered software development workflows that improve how engineering teams plan, write, test, review, debug, and deliver software. Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, workflow automations, and production accelerators—often using Codex as part of your own development process. Help customers progress from promising experiments to reliable production workflows, sustained developer adoption, and scaled impact across engineering organizations. Design systematic approaches for evaluating AI coding systems using representative software engineering tasks, automated graders, production signals, and developer feedback. Make sound technical decisions across models, agents, tools, developer environments, integrations, reliability, observability, latency, cost, safety, security, and operational readiness. Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive technical blockers toward resolution. Lead technical deep dives, workshops, and hands-on enablement that help engineering teams understand and adopt advanced AI coding workflows effectively and safely. Gather high-fidelity insights from real-world Codex deployments and translate them into clear product proposals, model feedback, and technical requirements for OpenAI Product, Research, and Engineering teams. Create reusable architectures, tooling, examples, guides, and technical patterns—including contributions to resources such as the OpenAI Cookbook—that accelerate future Codex deployments. Influence customer engineering strategy by helping technical leaders understand how AI coding systems can reshape their software development lifecycle, engineering practices, and organizational workflows.