Applied AI Engineer Codex
OpenAIVisit OpenAI website
AI research and deployment company building and deploying frontier AI products, including ChatGPT, Codex, and its API platform.
49 current maintainers29 active leads5 new active leads117 lead step-downs16 early lead departures
San Francisco, United States
Projects
About OpenAI
OpenAI’s mission is to ensure artificial general intelligence benefits all of humanity. It consists of the nonprofit OpenAI Foundation and OpenAI Group, a public benefit corporation governed by the Foundation.
Skills
About the Role
You will partner with engineering leaders and developers to design, prototype, evaluate, deploy, and scale AI-powered coding workflows. You will build integrations, automations, evaluation systems, and production accelerators; troubleshoot technical issues; lead workshops; and turn deployment insights into product feedback and reusable technical resources.
Requirements
- Demonstrated experience designing, building, and delivering software or AI systems in enterprise environments from prototype to production
- Substantial hands-on contributions in code, architecture, evaluation, debugging, integrations, or production engineering
- Proficiency in Python
- Experience using AI coding tools
- Ability to evaluate AI coding systems systematically
- Experience with enterprise production requirements including reliability, observability, security, privacy, data governance, performance, and cost
- Ability to lead technical workshops and hands-on sessions
- Fluency in English and French
Responsibilities
- Partner with engineering leaders and developers to identify Codex opportunities and define architectures, implementation plans, evaluation strategies, and success criteria
- Design, build, and deploy AI-powered software development workflows
- Build prototypes, evaluation harnesses, reference implementations, integrations, automations, and production accelerators
- Evaluate AI coding systems using representative tasks, automated graders, production signals, and developer feedback
- Make technical decisions involving models, agents, tools, reliability, observability, security, and operational readiness
- Diagnose implementation challenges and resolve technical blockers
- Lead technical deep dives, workshops, and hands-on enablement
- Translate deployment insights into product proposals, model feedback, and technical requirements
- Create reusable architectures, tooling, examples, guides, and technical patterns
- Influence customer engineering strategy for AI coding systems
Benefits
- Relocation assistance
