Design a Multi-Tenant Enterprise RAG Assistant: Hybrid Retrieval, Reranking, ACLs

Quick Overview

Design a multi-tenant retrieval-augmented generation assistant that answers employees' questions from their company's documents with citations. Cover ingestion and embeddings, hybrid keyword and vector retrieval with score fusion, reranking, permission-aware multi-tenancy, evaluation, and how to train or adapt embedding models.

Design a Multi-Tenant Enterprise RAG Assistant: Hybrid Retrieval, Reranking, ACLs

Company: OpenAI

Role: Machine Learning Engineer

Category: ML System Design

Difficulty: hard

Interview Round: Onsite

Overview: Design a multi-tenant retrieval-augmented generation assistant that answers employees' questions from their company's documents with citations. Cover ingestion and embeddings, hybrid keyword and vector retrieval with score fusion, reranking, permission-aware multi-tenancy, evaluation, and how to train or adapt embedding models.

OpenAI logo
OpenAI
Sep 20, 2026
hardMachine Learning EngineerOnsiteML System Design
33
0
Loading...