Databricks GenAI Engineer case studies
Databricks GenAI Engineer · Put your knowledge to work in context.
The Databricks Certified Generative AI Engineer Associate is a professional credential from Databricks that validates a practitioner's ability to design, build, evaluate, deploy, and govern generative AI applications on the Databricks Data + AI Platform. It is aimed at data engineers, ML engineers, solution architects, and application developers who already work with Spark, Delta Lake, and Unity Catalog and who now need to ship LLM-backed systems - retrieval-augmented generation pipelines, agentic workflows, and evaluation harnesses - rather than train models from scratch. The Databricks GenAI Engineer case studies are 5 cases and about 4,359 words.
1The 9-Second p95: A Support Copilot That Misses Its SLA
A retail support org runs an internal copilot on Databricks Model Serving, backed by a pay-per-token Foundation Model API endpoint for a 70B model. Peak traffic is about 40 requests per minute; overnight it drops to near zero, and the endpoint is configured to scale to zero.
862 words, about 4 min2Recall@5 of 41%: Contracts the Retriever Cannot Read
An ops team ingests 4,200 supplier contracts (PDF, 38 pages on average) into a RAG assistant. Roughly a fifth are scanned images.
883 words, about 4 min3The Judge Says 92%, Users Say Thumbs-Down
An HR policy assistant uses RAG over 900 internal policy pages. Before launch, the team ran an offline evaluation with an LLM judge prompted: "Is the answer supported by the retrieved context?" The judge scored 92% and the team shipped.
851 words, about 4 min4Silent Model Swap: Monitoring an Endpoint You Don't Control
A team serves a customer-facing assistant on a Databricks Model Serving endpoint that calls an external foundation model. Volume is 1.2M requests a month.
871 words, about 4 min5One Index, Two Clearances: Post-Filtering and a Prompt Injection
One Vector Search index over 60,000 support documents powers two products: an external chatbot for customers and an internal agent for support engineers. Source docs carry visibility (public/internal/restricted) and region columns, but both products query the index with the same service principal.
892 words, about 4 min