About the job
Uber's Developer Platform is in the middle of a paradigm shift. The industry moved from text editors to IDEs. We're now moving from IDEs to Agentic Dev Environments (ADEs), where AI agents are first-class participants in the software development lifecycle. The AI Foundations & Developer Experience (AIFX) team is building the infrastructure that makes this shift real. We own: The agent runtime. Claude Code, Codex, and Minions, our background agent orchestration system for autonomous code generation. The MCP platform layer. Giving agents structured access to Uber's tools, data, and developer lifecycle. The Skill Marketplace. Encoding tribal knowledge into loadable, composable expertise so any engineer can be instantly productive in any monorepo. We're hiring engineers who think in systems, not features. You'll own foundational pieces of Uber's agentic infrastructure. Getting it right means every team at Uber ships faster.
Responsibilities
Design and ship the skill pack framework. How skills are authored, versioned, distributed, and loaded across Go, Java, Python, iOS, Android, and Web monorepos. Skills are the differentiator: portable expertise that makes any agent instantly productive.
Build the multi-agent runtime inside Uber's DevPod cloud environments. Persistent background agents, swarm orchestration, cross-agent context passing. Agents working 24/7 in parallel, not one-shot interactions.
Develop AI-powered code intelligence. Semantic code search, dependency-aware context, codebase understanding that gives agents deep structural knowledge (not just text search).
Own and evolve the MCP platform layer. Consolidating code-mcp, docs-mcp, and developer lifecycle MCPs into a unified, low-latency context infrastructure that agents actually depend on.
Partner with Code Infra, DevPod, Mobile Platform, Web Platform, and Backend Platform teams to ship the foundational systems that make agentic engineering work at Uber's scale. ~5K microservices, 6 monorepos, 5,000+ engineers.
Set technical direction for agentic infrastructure across Uber's Developer Platform. Define the architecture, verification frameworks, and trust models for agent-generated code at org scale.
Mentor engineers in agentic fluency. Raise the bar on how teams think about, build with, and ship through AI agents.
Qualifications
Minimum
Experience building and scaling developer tooling or platform infrastructure (e.g., SDKs, CLIs, APIs, runtime systems) in large-scale engineering environments
Strong proficiency in at least one major programming language (Go, Java, Swift, Kotlin, Python, or TypeScript) with demonstrated experience integrating AI/ML models into developer workflows
System design experience for high-reliability, observable, developer-facing services and agentic systems
Preferred
Experience building and scaling developer tooling or platform infrastructure (e.g., SDKs, CLIs, APIs, runtime systems) in large-scale engineering environments
Strong proficiency in at least one major programming language (Go, Java, Swift, Kotlin, Python, or TypeScript) with demonstrated experience integrating AI/ML models into developer workflows
System design experience for high-reliability, observable, developer-facing services and agentic systems