How many GenAI questions are in this list?

25 questions, the highest rated GenAI AI interview questions.

Are these real AI interview questions?

Yes. Every question is sourced from real AI interview reports across companies like OpenAI, Anthropic, Google, Microsoft, and Cohere, then reviewed by senior AI engineers for accuracy.

Do these questions come with detailed answers?

Yes. Every entry links to a full answer with explanations, hints, key tradeoffs, and recommended follow up questions. Most also include difficulty ratings and community quality scores.

How is the ranking calculated?

Questions are sorted by community quality score, with rating count as the tiebreaker, then difficulty (easier first). Quality scores come from interview candidates rating each question after working through it.

Curated

Top 25 GenAI Interview Questions

Here are the top 25 GenAI interview questions on Zenaique, sorted by community quality and rating count. Each links to a detailed answer covering reasoning, tradeoffs, and follow up questions. Browse the full library →

Sorted by community quality, ties broken by rating count then easier first.

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01
Explain scaled dot product attention.
Short AnswerMedium Decagon Freshworks
02
What is the KV cache in transformer inference?
FlashcardEasy Elevenlabs Phonepe
03
What is RLHF, and why is it used after pretraining?
Multiple ChoiceEasy Cognizant Flowise
04
What does LoRA do, and why is it popular for fine-tuning?
Multiple ChoiceMedium Anduril Rephrase Ai
05
In LLM serving, what is the primary driver of end to end latency for a generation request?
Multiple ChoiceMedium Meta NVIDIA
06
Which metric best measures whether a RAG answer is grounded in the retrieved context?
Multiple ChoiceMedium Datadog IBM
07
Design a RAG evaluation harness, what do you measure and how?
Short AnswerHard N8n Redis
08
When should you fine-tune instead of using RAG?
Short AnswerMedium Kore Ai Persistent
09
Explain why transformers replaced RNNs for language modeling.
Short AnswerEasy Ironclad Together Ai
10
What does RAG primarily help with in LLM based applications?
Multiple ChoiceEasy Airbnb Perplexity
11
Why combine BM25 with dense embeddings for retrieval?
Multiple ChoiceEasy Anduril Crewai
12
PPO vs DPO, what's the practical difference?
FlashcardMedium Kpmg Sambanova
13
What is the Model Context Protocol (MCP) and what problem does it solve?
Multiple ChoiceEasy Accenture Dust
14
What distinguishes an AI agent from a plain LLM call?
Multiple ChoiceEasy Inflection Ai Mu Sigma
15
Which components make up a standard transformer block?
Multiple ChoiceEasy Goldman Sachs Mistral AI
16
Which of these are valid concerns when using LLM-as-judge for evaluation?
Multi-selectMedium Airbnb Labelbox
17
PremiumHNSW vs IVF, when…
FlashcardMedium Dust Goldman Sachs
18
How does MCP differ from OpenAI style function calling?
FlashcardMedium Phonepe Promptlayer
19
Match each vector index type to its primary characteristic.
Match PairsMedium Forethought Intel
20
Describe the typical agent execution loop.
Short AnswerMedium Forethought Runway
21
Which of these are valid considerations when choosing a chunking strategy for RAG?
Multi-selectMedium Ai21 Coinbase
22
Estimate the per call cost of a typical RAG chatbot using GPT-4o-mini.
FlashcardEasy OpenAI Pwc
23
Why is cosine similarity preferred over Euclidean distance for text embeddings?
FlashcardEasy Anthropic Cohere
24
Why does BPE tokenization use subwords instead of words or characters?
FlashcardEasy Meta OpenAI
25
What is the primary purpose of embeddings in modern NLP?
Multiple ChoiceEasy Amazon Perplexity

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