RAG Pipeline for AI Engineering
Build the data pipeline behind a RAG system — chunking, embedding, vector storage, retrieval, reranking.
About this project
RAG (Retrieval-Augmented Generation) pipelines are the new data-engineering specialty. This project teaches the full pipeline: document ingestion, chunking strategies, embedding generation, vector storage (pgvector or Qdrant), retrieval, and reranking. Build it on a real corpus — your company's docs, an open-source codebase, Wikipedia subset.
Why build this in 2026?
Every AI product has a RAG pipeline behind it. Data engineers who can build and maintain these have a sharp hiring advantage.
What you'll ship
- GitHub repo
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