Design a Retrieval-Augmented Generation (RAG) system

Quick Overview

This question evaluates a candidate's ability to design production-grade Retrieval-Augmented Generation systems, testing competencies in information retrieval, embedding and indexing strategies, LLM integration, scalability, access control, and observability within the ML system design domain.

Design a Retrieval-Augmented Generation (RAG) system

Company: OpenAI

Role: Software Engineer

Category: ML System Design

Difficulty: hard

Interview Round: Technical Screen

Quick Answer: This question evaluates a candidate's ability to design production-grade Retrieval-Augmented Generation systems, testing competencies in information retrieval, embedding and indexing strategies, LLM integration, scalability, access control, and observability within the ML system design domain.

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Dec 15, 2025, 12:00 AM
hardSoftware EngineerTechnical ScreenML System Design
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