Software Engineer, Codex — User Activation

OpenAI OpenAI · AI Frontier · San Francisco, CA · Applied AI

Software Engineer role focused on building full-stack product surfaces for user activation and adoption of the Codex AI software engineer product within enterprise organizations. This involves working on onboarding, integrations, discovery, and collaborative team experiences to turn initial usage into sustained adoption.

What you'd actually do

  1. Build onboarding, setup, and discovery experiences that help developers quickly connect Codex to their repositories, tools, environments, and existing workflows.
  2. Create product surfaces that help users discover Codex capabilities, including plugins, skills, integrations, templates, recommendations, and workflow entry points.
  3. Build collaborative team experiences that make Codex easier to adopt across organizations, including workspace setup, invitations, sharing, team-level configuration, and usage visibility.
  4. Develop full-stack systems across web, IDEs, CLI, and integrations, balancing polished user experience with reliable backend architecture.
  5. Partner with product and design to run experiments, understand activation funnels, identify adoption blockers, and iterate quickly based on real user behavior.

Skills

Required

  • strong full-stack software engineering fundamentals
  • experience building polished, production-grade user experiences
  • comfortable working across frontend and backend systems
  • experience building onboarding, activation, growth, collaboration, discovery, or developer-product experiences
  • care deeply about user experience
  • turn ambiguous customer problems into simple, intuitive product flows
  • enjoy working across product, design, engineering, analytics, and customer-facing teams
  • comfortable using data, experimentation, and user feedback to guide product decisions
  • enjoy 0 → 1 environments
  • move quickly through ambiguity
  • strong product judgment to technical trade-offs

Nice to have

  • React
  • TypeScript
  • Python
  • Go

What the JD emphasized

  • full-stack product surfaces
  • activation and adoption
  • connect it to the tools and codebases they already use
  • turn curiosity into repeatable value
  • systems end-to-end
  • production operations
  • onboarding, setup, and discovery experiences
  • product surfaces that help users discover Codex capabilities
  • collaborative team experiences
  • full-stack systems
  • run experiments, understand activation funnels, identify adoption blockers
  • customer adoption challenges
  • great onboarding, discovery, and activation

Other signals

  • building state-of-the-art AI systems
  • AI software engineer
  • product experiences that drive activation and adoption