I built a RAG pipeline from scratch, and one wrong answer made me dive even deeper into AI Engineering

A backend engineer's first step into AI Engineering: embeddings, vector search, and the chunking bug that made everything click.

Why I decided to pivot toward AI Engineering

I have been a backend engineer for a while now: TypeScript, NestJS, distributed systems, APIs in production. I like that work. But at some point I started paying attention to a specific career trajectory I came across: someone with a background almost identical to mine who had moved into AI Engineering. Not abandoned backend, extended it.

That reframed everything for me. This wasn't a pivot away from what I knew. It was a direction to grow into. And I decided to start from the fundamentals, not from the tooling.

So instead of installing LangChain and following a tutorial, I built a RAG pipeline from scratch, no abstractions, no magic. Just Python, the Gemini API, and ChromaDB. Here is what I learned.