Software Engineer Intern, AI Developer Productivity - Summer 2026

Hyperproof is reinventing how engineering teams build software in the age of AI. They are seeking a Software Engineer Intern to join their Engineering team for Summer 2026, focusing on AI-assisted development and internal tooling for enhanced developer productivity.

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 that raise the quality of AI output across the team
• Contribute to test impact analysis, flake quarantine, pipeline parallelization, and build acceleration to support higher AI-driven PR throughput
• 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 the AI-focused projects, you'll get scoped feature and bug-fix work in our TypeScript/Node.js/React frontend and Java/C# backend services — because the best way to understand a developer productivity problem is to be a developer working in the system
• Work directly with a mentor on real problems, write automated tests, and document what you build

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) — and opinions about where they shine and where they fall over
• 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 — a lot of AI productivity work is fundamentally about clearly conveying context, both to humans and to models
• Any experience with CI/CD systems, observability tooling, or building developer tools