I Cracked the EY GenAI Developer Interview — Here Are All 15 Questions They Asked Me (With Answers)

2026-04-25 · Source: Data Science on Medium · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Software Development & Engineering · Depth: Advanced, quick

Summary

An applicant for a GenAI Developer role at Ernst & Young (EY) underwent a 75-minute virtual technical interview. The interview focused on core Generative AI concepts, including transformer architecture and Retrieval-Augmented Generation (RAG) systems. The candidate described a RAG-based document intelligence project, detailing its architecture, which involved ingesting PDFs, semantic chunking, embedding with `text-embedding-3-small`, storing data in ChromaDB, and using a FastAPI backend to deliver grounded, cited responses via an LLM. The interview process was direct, with no small talk, immediately proceeding to technical questions.

Key takeaway

For AI Engineers preparing for GenAI developer interviews, you should meticulously prepare by revisiting transformer architecture and building practical RAG-based projects. Be ready to articulate your project's architecture, specific component choices like embedding models and vector databases, and how they contribute to grounded, cited responses.

Key insights

Technical interviews for GenAI roles demand deep knowledge of core architectures and practical application.

Principles

• Demonstrate project ownership
• Detail architectural choices

In practice

• Describe RAG-based systems
• Mention specific embedding models

Topics

• EY GenAI Developer Interview
• Retrieval-Augmented Generation
• Transformer Architecture
• Document Intelligence Systems
• ChromaDB

Best for: AI Engineer, Machine Learning Engineer, AI Student

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Editorial summary, takeaway, and curation by AIssential. Original article published by Data Science on Medium.