Source Development Internship

Alphashots.AI

RemoteFresher1h agovia Unstop

About the Role

Join Alphashots.AI for a paid, remote technical internship where you will contribute to UnvibeCode, our open-source AI-powered codebase understanding platform. This is a hands-on engineering opportunity to work on emerging AI developer technologies, including Model Context Protocol (MCP), OpenCode integration, LLM-based workflows, and code intelligence systems. You'll work on real engineering problems, contribute to a public GitHub repository, and build practical experience in AI Engineering.

Internship Details

  • Position: AI Engineering & Open-Source Development Intern
  • Duration: 1 month
  • Time commitment: 3–5 hours per week
  • Mode: Remote, Flexible
  • Stipend: ₹25,000–₹30,000 fixed per month
  • Eligibility: Engineering students (any stream), MCA/BCA, 2nd year onward
  • Open positions: 1–2

What You Will Work On

MCP (Model Context Protocol) Development

  • Build and test MCP server capabilities for exposing codebase analysis and developer tools to AI agents.
  • Implement tool interfaces that allow AI assistants to retrieve repository context, workflows, and code relationships.

OpenCode & AI Coding Tool Integration

  • Contribute to integrating UnvibeCode with OpenCode and AI-powered coding assistants.
  • Help AI coding agents access relevant code context and understand dependencies across repositories.

LLM Engineering & Context Optimization

  • Develop and test LLM-based workflows for code understanding, business workflow discovery, and technical risk analysis.
  • Explore context retrieval, prompt optimization, and techniques to reduce unnecessary LLM token consumption.

Python & Open-Source Engineering

  • Implement features, fix bugs, write unit tests, and improve existing Python modules.
  • Work with GitHub issues, pull requests, code reviews, and CI/CD workflows.

Code Intelligence & Repository Analysis

  • Contribute to AST-based code analysis, dependency mapping, and function-level code connections.
  • Test code understanding and repository analysis features against real-world open-source projects.

Assignments will be based on project priorities and the intern's technical capabilities.

Preferred Technical Skills

  • Programming: Working knowledge of Python and basic debugging.
  • Development tools: Familiarity with Git, GitHub, and pull requests.
  • AI fundamentals: Basic understanding of LLMs, AI agents, APIs, or RAG.
  • Problem-solving: Ability to read unfamiliar code, investigate bugs, and learn new technologies.

Prior experience with MCP or OpenCode is not mandatory. We value programming fundamentals, curiosity, and the ability to learn and build.

Rewards for Participants

  • ₹10,000 total prize pool: Shared equally among the top 4 rankers for the UnvibeCode Engineering Challenge.
  • Top 10 performers: Recommendation letters based on challenge performance.
  • Top 50 performers: Engineering Challenge participation and achievement certificates.
  • First 100 eligible participants: AI System Design Interview Preparation Pack.

What You Will Gain

  • Real-world AI Engineering exposure: Experience with technologies including MCP, LLM integration, AI coding agents, and context engineering.
  • Public GitHub contributions: An opportunity to build verifiable engineering work through open-source pull requests.
  • Practical software engineering experience: Work on real product features, debugging, testing, and code reviews.
  • Technical mentorship: Learn how AI developer tools are designed, built, tested, and improved.
  • Stronger technical profile: Demonstrate hands-on engineering contributions when applying for AI Engineering, Software Engineering, or FDE roles.

About Alphashots.AI

Alphashots.AI is an IIT–IIM-founded, pre-seed-funded AI technology startup developing applied machine learning solutions and open-source AI developer tools. Our open-source project, UnvibeCode, helps developers and AI coding assistants understand unfamiliar repositories by mapping business workflows, code dependencies, and technical risks.

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