Q: Data Engineer → AI Engineer

Your head start: RAG is a data pipeline. Ingesting documents, transforming them, chunking, embedding, loading into a vector database — this is ETL with new vocabulary, and you've built ETL for years. And when companies build AI systems, they consistently discover their real problems are data quality problems. That's your territory.

Your gap: the application layer. Data engineers build pipelines that feed systems; AI Engineers also build the system itself — the APIs, the app logic, the deployment. Expect to strengthen that side while the retrieval side comes naturally.