Generative AI System Design Interview

Designing generative AI (GenAI) systems for interviews can be complex and challenging. This book offers a clear and structured approach to help you tackle a wide range of GenAI system design questions. It provides a practical framework and real-world examples to make learning these concepts easier.

This book complements our ML System Design Interview book. While the first book focuses on topics such as search and recommendation systems, this one centers on generative systems, with detailed examples and explanations to help you understand how GenAI systems are built in practice.

What’s inside?

An insider’s perspective on what interviewers are truly looking for and why.

A 7-step framework to help you tackle GenAI system design interview questions.

10 real-world GenAI system design questions with in-depth solutions.

280+ diagrams to demystify complex GenAI systems.

About the authors

Hao Sheng

is a researcher and engineer specializing in AI and machine learning with over 10 years of expertise. He holds a Ph.D. in Computer Engineering from Stanford University and has worked at OpenAI, Apple, TikTok, and Landing AI. His expertise spans recommendation systems, computer vision, and generative AI. Hao has also taught "Search and Recommendation Systems" at Stanford.

Ali Aminian

is an author and a Staff ML engineer with +10 years of expertise working in tech companies (Adobe, Ex-Google) building large-scale and distributed ML systems.