Databricks GenAI Engineer Exam Guide 2026

This Databricks GenAI Engineer exam guide covers the Databricks Certified Generative AI Engineer Associate credential. According to the Databricks certification page, the exam has 45 scored questions and a 90-minute limit.

The exam tests whether you can design and build large language model solutions on Databricks. This guide covers what it measures, who it suits, and how to plan four weeks of preparation.

What is the Databricks Generative AI Engineer Associate exam?

It is the Databricks Certified Generative AI Engineer Associate exam. According to Databricks, it assesses your ability to design and implement LLM-enabled solutions using Databricks.

An LLM (large language model) is an AI model trained on large amounts of text that can generate and transform language. The exam covers problem decomposition, which means breaking a complex requirement into manageable tasks, and choosing appropriate models, tools and approaches.

It is a proctored exam with multiple-choice questions. Databricks lists no prerequisites, but it highly recommends related training.

What does the Databricks GenAI Engineer exam guide cover?

The exam covers six domains, and Application Development carries the most weight at 30%. Databricks publishes these percentages on the certification page.

Domain	Weight
Design Applications	14%
Data Preparation	14%
Application Development	30%
Assembling and Deploying Apps	22%
Governance	8%
Evaluation and Monitoring	12%

Application Development and Assembling and Deploying Apps together make up just over half of the exam, so most of your hands-on time belongs there. Governance is the smallest domain at 8%, which makes it tempting to skip, but a few questions on it can still decide a close result.

Which Databricks tools does the exam assess?

Databricks names four tools on its certification page. AI Search handles semantic similarity searches, Model Serving deploys models and solutions, MLflow manages a solution lifecycle, and Unity Catalog covers data governance.

RAG (retrieval-augmented generation) is a pattern where a model answers using documents retrieved at question time instead of relying only on its training data. Databricks says people who pass can be expected to build and deploy performant RAG applications and LLM chains.

Which language does the code use?

Databricks says all machine learning code in the exam is in Python. For workflows or code not specific to machine learning tasks, data manipulation code could be provided in SQL.

Practise reading short scripts and predicting their output. Test aides are not allowed, so you cannot look anything up.

Who is the Databricks GenAI Engineer exam for, and who is it not for?

It suits people who already build with generative AI, or are about to, on the Databricks platform. Databricks recommends 6+ months of hands-on experience performing the generative AI solution tasks in the exam guide.

It is a good fit for:

• developers and data scientists moving into LLM application work on Databricks;
• engineers from other platforms who want to show they can build RAG applications in the Databricks workspace;
• team members who deploy, evaluate and monitor LLM chains in production.

It is a weaker fit for:

• people looking for a purely conceptual overview of generative AI with no hands-on work;
• readers who first want to judge whether credentials are worth the time, who can start with our post on whether AI and data certifications are worth taking.

How should you use this exam guide? A 4-week plan

Plan around the weights: development, assembly and deployment are over half of the exam. This plan assumes about six hours a week.

1. Week 1: design and data preparation. Practise breaking a business request into tasks and choosing a model and approach for each. Then prepare documents so a retrieval step can find them.
2. Week 2: application development. Build a RAG application and an LLM chain end to end. Use AI Search for semantic similarity searches and change one design choice at a time to see its effect.
3. Week 3: assembly and deployment. Deploy a solution with Model Serving and track its lifecycle with MLflow. Read every line of the Python you write.
4. Week 4: governance, evaluation and timed practice. Review governance with Unity Catalog and practise evaluating and monitoring a solution. Finish with full timed practice tests, review every miss by domain, and repeat.

Spaced, mixed review beats rereading; our post on how to study for a technical exam explains why.

How are the questions delivered?

The exam is a proctored certification with multiple-choice questions. Databricks says you can take it online or at a test center, and that no test aides are allowed.

For an online exam, the certification page asks you to review the technical requirements and run a system check first. Registration happens on Databricks’ exam delivery platform.

It is offered in English, Japanese, Portuguese (Brazil) and Korean. The registration fee is $200.

How long is the certification valid, and how do you renew it?

The validity period is 2 years, according to Databricks. To recertify, you take the current version of the exam.

That means the exam you sit in two years may not match today’s outline. Databricks tells you to review the exam guide again to find gaps before you prepare for a recertification exam.

Is the Databricks GenAI Engineer exam hard?

It is manageable if you have built retrieval applications and deployed them, and difficult if you have only read about generative AI. The questions are multiple choice, but the scenario items reward hands-on experience.

Two things raise the difficulty. The generative AI landscape moves quickly, so a study source from a year ago may use outdated terms. And with a 90-minute limit for 45 scored questions, you need to read scenarios quickly.

How do you know you are ready to book?

You are ready when you can walk through each domain without notes and explain why you would choose one approach over another. Use Databricks’ AI Prep Guide first to learn the question style.

Then sit at least two full timed Databricks Generative AI Engineer practice tests and look at your score by domain, not only the total. If one domain trails, spend another week building before you book.

Before you schedule, recheck the Databricks certification page for the current domains, price and any update.

Related reading

• Databricks Data Engineer Associate exam guide 2026
• Are AI and data certifications worth taking in 2026?
• What blueprint-aligned practice tests actually mean
• Google Cloud Generative AI Leader practice exam guide
• All CertCrafter articles