Interview
Questions
AI Application Engineer Interview Questions
Behavioral questions for AI/ML engineers building LLM applications, RAG systems, and AI agents. Covers hallucination handling, prompt engineering, token optimization, and production AI challenges.
How have you evaluated LLM outputs for quality in production? What metrics or approaches did you use?
Describe your approach to testing and validating AI features before shipping. How do you handle non-deterministic outputs?
Tell me about a time you had to handle hallucinations in an LLM application. What strategies did you use to detect and mitigate them?
How have you approached prompt engineering for a production system? What iteration process did you follow to improve results?
Tell me about an AI agent or multi-step LLM system you designed. What were the key architectural decisions and why?
Tell me about a RAG system you built or improved. What challenges did you face with retrieval quality and how did you address them?
How have you approached safety and content moderation in AI applications? Give a specific example.
Tell me about an AI or ML project you have shipped to production. What challenges did you face?
Describe a time when you had to explain complex AI concepts to non-technical stakeholders.
How do you approach evaluating whether AI is the right solution for a given problem?
Tell me about a time when an ML model did not perform as expected in production. How did you debug it?
How do you stay current with the rapidly evolving AI landscape?