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Design a RAG System is a medium system design interview question covering Distributed Systems, vector search, machine learning, nlp — the kind asked at FAANG (Facebook/Meta, Apple, Amazon, Netflix, Google) and AI-first companies like Anthropic, OpenAI, and Nvidia.
Design a retrieval-augmented generation (RAG) system for an enterprise knowledge assistant: 10 million documents (wikis, PDFs, tickets) with per-user access permissions inherited from source systems, 100,000 queries per day, answers streaming within about a second, citations required, and document edits retrievable within minutes. A user must never receive an answer derived from a document they cannot open, and when the corpus does not contain the answer the system must say so rather than guess.
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