Build a small in-memory document indexer and retriever from scratch (inverted index + BM25), then add a vector option.
A bridge connecting classic DSA and modern RAG. Interviewers want to see you build a working inverted index and a correct BM25 score by hand, reason about its complexity, and then know precisely when you would switch to embeddings and an ANN index instead.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
A bridge connecting classic DSA and modern RAG. Interviewers want to see you build a working inverted index and a correct BM25 score by hand, reason about its complexity, and then know precisely when you would switch to embeddings and an ANN index instead.
Lead with where the obvious approach breaks, because that is the judgment they are screening for — most candidates jump straight to the happy path and lose the room.
Then walk the failure back through the pipeline in order, naming the one metric the customer's exec sponsor actually cares about before you propose the fix.
