Problem
Scenario
You're discussing work where a language model needs to answer questions using a trusted internal knowledge base instead of relying only on pretraining. The conversation is focused on how you have built or would build GenAI systems that combine retrieval, prompting, and evaluation.
Question
What is your experience with GenAI, RAG architecture, and prompt engineering?
What This Tests
- Designing a Retrieval-Augmented Generation pipeline
- Prompt engineering for grounded answers and refusal behavior
- Vector search and retrieval quality trade-offs
- Evaluation of LLM outputs for correctness and faithfulness
Practicing as: Data Scientist interview at Arthur J. Gallagher &Hi, I'll play your Arthur J. Gallagher & interviewer for the Data Scientist role. Answer the question above like we're in the room, and I'll respond the way a real interviewer would.
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