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AI Engineer Interview
Definition
AI Engineer interviews typically include system design for AI applications, coding challenges involving LLM integration, prompt engineering exercises, and discussions of RAG architecture and agent design patterns.
Common Interview Components
System Design:
- Design a RAG system for [specific use case]
- Design a customer support agent architecture
- How would you handle [specific AI challenge]?
Coding:
- Implement a basic RAG pipeline
- Write a prompt that handles [specific task]
- Debug an LLM integration issue
Conceptual:
- Explain embeddings and how they work
- Compare RAG vs fine-tuning for a given scenario
- Discuss evaluation strategies for LLM applications
Behavioral:
- Tell me about an AI project you’ve built
- How did you handle an edge case in production?
- Describe a time you had to explain AI limitations to stakeholders
Preparation Tips
Build projects that demonstrate end-to-end AI engineering: a RAG system, a simple agent, or an AI-powered feature. Be ready to discuss architecture decisions, tradeoffs you made, and how you measured success. Practice explaining technical concepts clearly - many interviews assess communication skills alongside technical ability.