Databricks AI Engineer Interview Questions
The questions to prepare for a Databricks AI Engineer interview. Questions from real interview reports rank first. Updated weekly.
Design monitoring for a Databricks RAG app where retrieval hit@5 and groundedness are falling while latency stays flat.
DatabricksDesign remote Terraform state, locking, and promotion workflows for reusable Databricks pipeline infrastructure across multi-env AWS deployments.
DatabricksCompare when to fine-tune a foundation model versus relying on prompt engineering with a managed API.
DatabricksTests your ability to design reliable context handling for multi-turn LLM systems.
DatabricksCount recurring high-confidence ticket themes in April using joins, filtering, and grouped aggregation.
DatabricksPlan a 10-week launch for a Databricks-native RAG support agent while aligning executives, security, and engineering on scope trade-offs.
DatabricksDatabricks-native RAG design with Spark ETL, Vector Search, DBRX/FM serving, and MLflow Agent Evaluation under strict SLOs.
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Clean raw status text with TRIM and LOWER, filter unusable rows, and count usable events by cleaned status.
DatabricksRank the three most active Databricks users per day with aggregated counts and RANK to preserve ties.
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