Build a minimal RAG pipeline end to end: embed, index, retrieve, ground, and cite.
Everyone can write the happy path. The screen is decided by the two branches most candidates skip: what the system does when retrieval finds nothing good, and what it does when the model cites a chunk you never sent.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
Everyone can write the happy path. The screen is decided by the two branches most candidates skip: what the system does when retrieval finds nothing good, and what it does when the model cites a chunk you never sent.
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.
