Job Role: AI Developer Intern (LLM + MCP + AI Trends)
• 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
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AI Development (Primary Focus)
• Build applications using: OpenAI, Anthropic, Google DeepMind
• Implement: Tool/function calling, Context handling, Prompt pipelines
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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
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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
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Filter: What is useful vs hype
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Rapid Prototyping
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Build quick POCs using new tools
• Example: Try new model → integrate → test → report
• Convert useful tools into: Internal features, Product improvements
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Weekly Intelligence Reports
• Share: 5–10 new tools, 2 tools worth implementing, 1 working demo/POC
Requirements
• 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
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Builds side projects
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Actively explores new AI tools
• Thinks: “How can I use this in real product?”
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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