AI Development Engineer Intern

Key Responsibilities

- Ship features on either side of the stack — gateway routing, MCP servers, agent workflows, knowledge base, or a user-facing AI feature.

- Build the evals that prove a prompt or retrieval change actually helped, before it reaches users.

- Prototype in days, then add the tests and logging that let it run unattended in production.

- Pull adoption, cost, and quality data, and report what you find — including when it contradicts the story.

- Talk to the people using what you build, internal or external; their complaints are the roadmap.

Requirements

Must have

- Built something real with LLM APIs: prompting, streaming, tool calling, failure handling.

- Git, tests, and debugging to root cause instead of guessing.

- SQL and enough data sense to spot an outlier skewing an average.

Nice to have

- Agent frameworks or MCP; daily use of coding agents (Claude Code, Cursor).