Responsibilities Ship measurable improvements to developer productivity (e.g., PR cycle time, CI duration, AI-assisted PR throughput) Write clean, well-tested code with thoughtful unit and integration coverage Contribute to Hyperproof's internal developer documentation, CLAUDE.md skill files, and MCP server configurations Work with Claude Code and GitHub Copilot day-to-day, and help evaluate tools like CodeRabbit for automated code review and PR summarization Help build automated agents for customer bug triage, PR regression classification, and error-to-fix workflows that chain multiple AI agents together Author and maintain CLAUDE.md skill files, MCP server configurations, and prompt engineering improvements Contribute to test impact analysis, flake quarantine, pipeline parallelization, and build acceleration Help provision multi-environment dev setups, authenticated MCP servers, and connected documentation that enable agentic coding workflows Build dashboards and instrumentation tracking PR throughput per developer, Claude usage rates, code coverage, and developer experience sentiment Explore using AI to automatically diagnose production errors from telemetry and propose or generate fixes Alongside AI-focused projects, get scoped feature and bug-fix work in TypeScript/Node.js/React and Java/C# Requirements Currently pursuing a degree in Computer Science, Computer Engineering, or a related applied sciences discipline Hands-on familiarity with at least one AI coding assistant (Claude Code, Copilot, Cursor, or similar) Solid fundamentals in at least one modern language (TypeScript, Python, Java, C#, or Go) and comfort with Git and the command line Curiosity about prompt engineering, agentic systems, MCP, and the broader question of how to make engineers more effective Familiarity with REST APIs and a willingness to learn new technologies quickly Strong written communication skills #J-18808-Ljbffr
