Description

• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience. AI Tool Knowledge and Fluency (Required) — must demonstrate at least 12 months daily use
• Daily active use of at least TWO of the following AI coding tools on production work in the last 12 months: GitHub Copilot, Cursor, Claude Code, Windsurf (formerly Codeium), Aider, Continue.dev, Sourcegraph Cody, Tabnine, Replit Agent, JetBrains AI Assistant.
• Comfortable with AI-driven code review — has used GitHub Copilot Code Review, CodeRabbit, Greptile, Qodo (formerly Codium), or similar tools, AND understands their limits.
• Has worked with AI agents for coding — i.e., tools that take a task and execute multiple steps (write code, run tests, fix errors, submit pull request) autonomously. Examples: Claude Code in agent mode, Cursor's Agent mode, Devin, OpenHands, Aider in architect mode.
• Comfortable writing effective prompts for code generation — including providing context files, defining constraints, and specifying output formats.
• Understands the concept of MCP (Model Context Protocol) — the standard for connecting AI tools to external data sources, codebases, and tools. Bonus if they've used or built MCP servers.
• Can describe specific failure modes of AI-generated code they have encountered — security issues (e.g., hardcoded secrets, SQL injection in generated queries), performance issues (e.g., N+1 queries, inefficient loops), and architectural issues (e.g., violating existing patterns).
• Understands prompt injection as a security risk and knows how to mitigate it in AI-augmented systems.
• Familiarity with evaluation ("eval") frameworks for AI output — knows that production AI features need automated tests, not just manual review

Key Skills

Education

Bachelor's degree