Top 30 Generative AI and LLM Interview Questions
The most frequently asked questions on this topic across all roles and companies, ranked by real interview frequency. Updated daily.
Explain how to evaluate a generative model using offline and online methods, with attention to hallucination, product metrics, and experiment design.
CACI
Capgemini
American AirlinesExplain LLM hallucination and give three practical ways to reduce it using grounding, prompting, and evaluation.
ClickUp
Roche
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Design a grounded document Q&A system and explain how vector search improves retrieval quality, latency, and hallucination control in RAG.
Booking
Front
Pratt & WhitneyDesign a high-throughput RAG pipeline that grounds answers, detects unsupported claims, and balances quality, latency, and cost.
LexisNexis Legal & Professional
RyanHHearingLifeReduce hallucinations in a RAG system even when retrieval is already correct, using grounding, verification, and evaluation.
Frontier Technology
Leidos
AperiaCompare RAG and fine-tuning, and decide when each is the better fit for an LLM product.
VirtusaOOracle Health
LiteraExplain a practical approach to fine-tuning an LLM for a specific task, including data, evaluation, and hallucination risks.
Ernst & Young
XometryPPSEGExplain how to manage memory, summarization, retrieval, and safety in a long-running LLM agent when context exceeds the model window.
MiraklAAivar
Humana