DATABRICKS-GENAI-ENGINEER-ASSOCIATE: Certified Generative AI Engineer Associate

About the DATABRICKS-GENAI-ENGINEER-ASSOCIATE Exam

Master the Databricks Certified Generative AI Engineer Associate exam (18 March 2026 guide) — designing GenAI applications, preparing data for retrieval-augmented generation (RAG), and building, deploying, governing, evaluating and monitoring LLM and agent applications on the Databricks Data Intelligence Platform with Mosaic AI Vector Search, Foundation Model APIs, the Mosaic AI Agent Framework and Agent Bricks, Model Serving, the AI Gateway, and MLflow 3.

The complete practice exam for the Databricks Certified Generative AI Engineer Associate certification (current 18 March 2026 exam guide). Covers designing GenAI applications (decomposing business requirements into GenAI tasks, choosing between RAG, fine-tuning and prompt engineering, selecting foundation and embedding models from Foundation Model APIs, and choosing Agent Bricks patterns — Knowledge Assistant, Multi-Agent Supervisor, Information Extraction — versus the code-first Mosaic AI Agent Framework), data preparation for RAG (document loading and parsing, chunking strategies and overlap, embedding-model selection, building standard and storage-optimized Databricks Vector Search indexes with Delta Sync, retrieval-quality evaluation, synthetic evaluation datasets, and Delta Lake as the data foundation), application development (prompt engineering, building RAG pipelines, agentic apps with tool calling, multi-agent designs with Genie Spaces, LangChain and LangGraph on Databricks, MLflow 3 Tracing, AI Gateway guardrails and PII handling, hallucination mitigation and grounding, and the AI Playground), assembling and deploying applications (logging chains and agents as MLflow models registered in Unity Catalog, real-time Mosaic AI Model Serving endpoints, storage-optimized Vector Search with hybrid search and reranking, MCP servers, the MLflow Prompt Registry with champion-challenger aliasing, Databricks Apps for agent UIs, CI/CD with Databricks Asset Bundles, AI Gateway rate limiting and inference tables, and blue/green and shadow deployment), governance (Unity Catalog access controls, row filters and column masks for PII, data and model lineage, responsible-AI guardrails, and compliance and audit controls), and evaluation and monitoring (offline evaluation with mlflow.genai.evaluate() built-in LLM judges and custom Scorers, Review Apps for human feedback, AI Gateway usage and inference tables, and Lakehouse Monitoring for drift) — every question a real-world scenario with full explanations.

Who Should Take This Exam?

The Databricks Certified Generative AI Engineer Associate is designed for generative-AI and machine-learning engineers, data scientists, and platform engineers who build and ship LLM-powered and agentic applications on the Databricks Data Intelligence Platform. It validates practical skills across RAG design and data preparation, Mosaic AI Vector Search and Foundation Model APIs, agent development with the Mosaic AI Agent Framework and Agent Bricks, deployment with Model Serving and the AI Gateway, Unity Catalog governance, and GenAI evaluation and monitoring with MLflow 3. Most hands-on work on the exam is in Python.

Prerequisites: None (6+ months of hands-on experience building generative AI solutions on Databricks recommended)

Typical study time: 4-8 weeks of focused study

Exam Quick Facts

Exam Domains & Weights

The DATABRICKS-GENAI-ENGINEER-ASSOCIATE exam covers 6 domains. Focus your study time based on the weights below — higher-weighted domains have more exam questions.

💡 Study tip: Application Development (30%) and Assembling & Deploying (22%) are more than half the exam, so build one agent end-to-end at least once: wire Databricks Vector Search and RAG into the Mosaic AI Agent Framework (or an Agent Bricks pattern), instrument it with MLflow 3 Tracing, log and register it in Unity Catalog, deploy it on Model Serving or Databricks Apps, and front it with the AI Gateway. Know the March-2026 additions cold — MLflow 3 (Tracing, Scoring, the Prompt Registry), MCP servers, storage-optimized Vector Search, and AI Gateway inference/usage tables — and use MLflow 3 GenAI APIs (mlflow.genai.evaluate() with built-in judges and custom Scorers), not the legacy Agent Evaluation framework. The two 14% design and data-prep domains reward knowing when to choose RAG vs fine-tuning vs prompting and how chunking, embeddings, and index type affect retrieval. Governance (8%) is the smallest domain but tests Unity Catalog controls, PII handling, and lineage for AI assets.

Practice Exam — 250 Questions

Prepare for the DATABRICKS-GENAI-ENGINEER-ASSOCIATE with our 250-question practice exam covering all 6 exam domains. Every question includes detailed explanations and maps to official exam objectives.

What you get:

• ✅ Exam simulation mode with timer
• ✅ Spaced repetition for weak areas
• ✅ Detailed explanations for every question
• ✅ Progress tracking across domains
• ✅ 20 free questions — no account needed

Databricks Certification Path

Start with the Data Engineer Associate or Machine Learning Associate, then take this Generative AI Engineer Associate to specialize in LLM and agent applications, and advance to the Professional tracks (Machine Learning Professional, Data Engineer Professional).

Study Tips

1. Build one agent end-to-end — the fastest way to internalize the 52% of the exam in Application Development and Deployment
2. Use our practice exam — try the 20 free questions first to gauge your readiness
3. Review explanations — don’t just check if you got it right; read why each answer is correct
4. Simulate exam conditions — use the timed exam mode to practice under pressure
5. Check the official page — official exam details always have the latest objectives