AI Engineer Interview Prep
AI engineers build applications powered by large language models and generative AI. Interviews cover prompt engineering, RAG systems, evaluation, and production deployment of LLM features.
Practice This Interview with AI — FreeKey Skills to Highlight
Common Behavioral Questions
Tell me about an LLM feature you shipped. How did you evaluate its quality?
Describe a time you had to debug a hallucinating or misbehaving LLM in production.
How do you decide between fine-tuning, RAG, and prompt engineering?
Walk me through how you've balanced LLM cost with feature quality.
Describe a feedback loop you built to improve an AI product over time.
Role-Specific Questions
Design a retrieval-augmented generation system for a customer support product.
How would you evaluate an LLM feature without a ground-truth dataset?
Explain the trade-offs between different embedding models.
Walk me through how you'd handle rate limits and fallbacks when calling LLM APIs.
How do you mitigate prompt injection and data exfiltration risks?
Interview Tips
Stay current — the AI ecosystem moves weekly
Have strong opinions on eval — AI interviews probe this hard
Prepare examples of shipped LLM features with measurable outcomes
Be ready to discuss cost, latency, and quality as a three-way trade-off
Know the safety and security dimensions (prompt injection, PII leakage)
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