AI Tools & Automation Intern (Developer)

Requirements

• Python or JavaScript programmingMust
• API understanding and integrationMust
• Basic LLM knowledge: tokens, context windows, and prompting techniquesMust
• Understanding of MCP (Model Context Protocol) and tool calling conceptsMust
• Knowledge of how LLM applications work end-to-endMust
• Proficiency with Cursor or similar AI-assisted development toolsMust
• Experience building side projects and shipping featuresMust
• RAG (Retrieval Augmented Generation) and vector database experience
• FastAPI or Node.js backend development
• GitHub projects and version control experience

What you'll do

• Build applications using OpenAI, Anthropic, Google DeepMind
• Implement tool/function calling, context handling, and prompt pipelines
• Build and maintain MCP (Model Context Protocol) servers
• Design multi-step workflows and structured outputs for LLM systems
• Stay updated with new AI tools, model updates, and development frameworks
• Track AI tools and releases from sources including Twitter, Product Hunt, and GitHub
• Filter and evaluate new AI tools to distinguish useful tools from hype
• Build rapid prototypes and proofs of concept using new AI tools
• Produce weekly intelligence reports with 5-10 new tools, 2 implementation recommendations, and 1 working demo
• Convert useful tools into internal features and product improvements

About the role

Job Role: AI Developer Intern (LLM + MCP + AI Trends) Role Overview: We are hiring an AI Developer Intern who can both: • Build AI systems (LLMs, MCP servers, APIs) • Continuously track and evaluate new AI tools & releases This is a builder + researcher hybrid role, but execution > research. Key Responsibilities: • AI Development (Primary Focus) • Build applications using: OpenAI, Anthropic, Google DeepMind • Implement: Tool/function calling, Context handling, Prompt pipelines • MCP Server & AI Systems • Build and maintain MCP (Model Context Protocol) servers • Create tools that LLMs can use: APIs, Internal systems • Design: Multi-step workflows, Structured outputs • AI Tools & Trends Tracking (Important) • Stay updated with: New AI tools launches, Model updates, Dev frameworks • Sources to track: Twitter (AI builders), Product Hunt, GitHub trending • Filter: What is useful vs hype • Rapid Prototyping • Build quick POCs using new tools • Example: Try new model → integrate → test → report • Convert useful tools into: Internal features, Product improvements • Weekly Intelligence Reports • Share: 5–10 new tools, 2 tools worth implementing, 1 working demo/POC Requirements Required Skills: • Must-Have: Python or JavaScript (strong basics), API understanding, Basic LLM knowledge: Tokens, Context Prompting, Critical (Filter Here), Can build, not just explore, Understands: MCP / tool calling, How LLM apps actually work, Cursor, Antigravity • Good to Have: RAG / vector DB, FastAPI / Node backend, GitHub projects Ideal Candidate: • Builds side projects • Actively explores new AI tools • Thinks: “How can I use this in real product?” • Not a YouTube learner, a doer Highlights Build LLM apps & MCP servers, test latest AI tools, ship real features, work closely with founders, fast growth, real product impact Originally posted on Himalayas