How to Validate LLM Output in a DuckDB and dbt Pipeline

A data pipeline was enhanced with an AI enrichment step to extract structured information from remote job postings. The process uses the Gemini Flash-Lite model to pull skills, seniority, and location eligibility from job descriptions managed with DuckDB and dbt. A crucial part of the implementation involves validating the LLM's output by forcing it to provide direct quotes as evidence for its claims, which are then programmatically checked. This validation step proved essential for catching model errors, identifying bugs in the data pipeline, and uncovering issues with source data quality like incorrect character encoding.