Databricks Certified Generative AI Engineer Associate Quick Facts (2025)

Databricks Certified Generative AI Engineer Associate Exam Overview

Struggling to prepare for the Databricks Certified Generative AI Engineer Associate exam? This guide breaks down everything you need to know — from exam structure and domains to common pitfalls and preparation tips.

What is the Databricks Certified Generative AI Engineer Associate Certification?

The Databricks Certified Generative AI Engineer Associate certification validates your ability to build and deploy LLM-enabled applications using the Databricks platform. It emphasizes your understanding of prompt engineering, Retrieval-Augmented Generation (RAG) applications, LLM chains, model governance, and the use of Databricks-specific tools such as Vector Search, MLflow, Unity Catalog, and Model Serving.

It is ideal for professionals who apply generative AI tools to real-world problems using the Databricks ecosystem.

Who Is This Certification For?

This certification is tailored for:

• Data professionals building scalable generative AI applications
• Developers incorporating LLMs and prompt engineering in production workflows
• Machine learning engineers integrating model deployment and governance
• Cloud engineers working on LLM chaining, data preparation, and orchestration
• Technical users using Databricks features like Vector Search or MLflow in generative AI pipelines

Even professionals in related fields such as NLP research, applied data science, and MLOps can benefit.

What Jobs Can I Get with This Certification?

Earning this certification can help you qualify for roles like:

• Generative AI Engineer
• Machine Learning Engineer
• AI Application Developer
• LLM Engineer
• Solutions Architect (AI/ML)
• Data Scientist with focus on LLMs and RAG
• AI Product Engineer

Organizations increasingly list this certification as a desired skill in job postings involving generative AI and the Databricks platform.

What version of the exam should I take?

This guide covers the current version of the Databricks Certified Generative AI Engineer Associate exam that is live as of June 1, 2024. Always verify the most updated exam guide two weeks before your test.

How much does the exam cost?

The registration fee for the Databricks Generative AI Engineer Associate exam is $200 USD. Local taxes may apply. Scheduled promotions or bundling discounts may occasionally be available via Databricks Academy.

How many questions are on the exam?

The exam includes 45 multiple-choice scored questions. In addition, Databricks may include a few unscored pilot questions for future test development.

How much time is given for the exam?

You have 90 minutes to complete the exam. Time is sufficient for reading, reasoning through prompts, and managing any unscored extras.

What languages is the exam available in?

The exam is offered in:

• English
• Japanese (日本語)
• Korean (한국어)
• Brazilian Portuguese (Português BR)

What's the passing score?

You must score 70 out of 100 to pass. All questions carry equal weight, and only scored items contribute to your final result.

Is the exam hard?

While this is an associate-level certification, it tests practical skills like chaining LLM components, crafting effective prompts, embedding model decisions, and deploying full-stack generative AI pipelines on Databricks.

Candidates who succeed often report 6+ months of hands-on experience plus structured study. Use high-quality, realistic Databricks Certified Generative AI Engineer Associate practice exams to diagnose gaps and gain the confidence for real exam conditions.

What domains does the exam cover and what are their weightings?

The exam is structured into six major domains with the following weightings:

1. Design Applications (14%)

   • Prompt formatting and model-task alignment
   • Translating use cases into pipeline structure
   • Selecting tools and chain components

2. Data Preparation (14%)

   • Chunking strategy
   • Retrieval quality vs. document structure
   • Writing chunked data to Delta Lake with Unity Catalog
   • Prompt/response quality
   • Extraction libraries

3. Application Development (30%)

   • LangChain or tool selection
   • Prompt optimization and adaptation
   • Agent construction
   • Embedding model selection
   • Safe model behavior (guardrails and mitigations)

4. Assembling and Deploying Applications (22%)

   • RAG pipeline components
   • Deploying pyfunc models
   • Model registration, Vector Search indexing
   • Deployed endpoint configuration

5. Governance (8%)

   • Guardrail design
   • Legal/licensing mitigation
   • Data masking strategies

6. Evaluation and Monitoring (12%)

   • LLM performance metrics and logging
   • MLflow experiment tracking
   • Operational monitoring and cost controls

Are there any prerequisites?

There are no strict prerequisites. However, Databricks recommends:

• 6+ months hands-on experience designing and deploying generative AI solutions
• Familiarity with:
  • Prompt engineering fundamentals
  • LangChain or equivalent libraries
  • LLM features, context lengths, and evaluation
  • Python (especially for model pipelines and app orchestration)
  • Databricks-native tools like MLflow, Unity Catalog, Vector Search, and Model Serving

What knowledge areas should I focus on?

To maximize your prep efforts, focus on:

1. Prompt Engineering

   • Meta-prompts and safety optimization
   • Chain architecture and multi-stage prompts
   • Tool-augmented prompt design

2. Data & Retrieval

   • Chunking strategies and document filtering
   • Retrieval accuracy metrics
   • Embedding model selection and vector storage

3. App Building with LangChain

   • Retriever and chain creation
   • Agent prompt templates
   • Context injection and few-shot learning

4. Model Deployment

   • Model packaging into pyfunc
   • MLflow registration
   • Foundation model APIs
   • Inference cost strategies

5. Security & Compliance

   • User input filtration
   • Mitigating data leakage
   • Legal safeguards on data use

6. Monitoring & Evaluation

   • MLflow-based experiment tracking
   • Logging inference requests
   • Model benchmarking and error analysis

Common Mistakes to Avoid

Avoid these common errors shared by past test takers:

• Underestimating prompt usefulness — prompt design is foundational
• Not practicing full-stack development — data prep to deployment must be understood end-to-end
• Neglecting evaluation techniques like MLflow logging and performance metrics
• Focusing only on tooling like LangChain without the underlying logic
• Overlooking governance and trust — safety, data masking, and legal filters are tested

Use practical, full-length Databricks GenAI Engineer practice tests to reinforce your holistic understanding of each domain.

How can I prepare for the exam?

Databricks and its partners offer several helpful resources:

1. Training Courses

   • Instructor-led: "Generative AI Engineering With Databricks"
   • Self-paced: Four core modules available:
     • Generative AI Solution Development (RAG)
     • Generative AI Application Development (Agents)
     • Generative AI Application Evaluation and Governance
     • Generative AI Application Deployment and Monitoring

2. Hands-On Labs

   • Use the Databricks Community Edition or your workspaces to build applications
   • Process documents, embed inputs, and deploy chains

3. Docs and Reference

   • Review official Databricks documentation
   • Study LangChain docs and open-source tools like Hugging Face Transformers

4. Practice Exams

   • Simulate real-world testing conditions
   • Identify weak areas before exam day
   • For best-in-class simulations, real LLM scenarios, and expert-written explanations, visit our Databricks Certified Generative AI Engineer Associate practice exams.

How long is the certification valid?

The certification is valid for 2 years from the date you pass. After this period, you need to retake the most current version of the exam to retain your certification.

What Should I Take After This Associate-Level Exam?

Once certified, you can expand your credentials with:

• Databricks' more advanced training in Generative AI Architectures
• Architect- or Solutions-level certifications when released
• Certifications from other cloud platforms like Azure or GCP for LLM integration

Maintaining your skills in governance, toolchains, and performance evaluation is essential as the GenAI space evolves.

Where can I take the exam?

You have one delivery option:

• Online Proctored Testing
  • Take it from your home or office
  • Requires webcam, internet access, and quiet space
  • No external test aides, papers, or books allowed

How do I register for the exam?

Steps to register:

1. Visit the official Databricks Generative AI Engineer Associate exam page
2. Choose your desired language and preferred date/time
3. Pay the exam registration fee
4. Run a system check to meet technical requirements
5. Review the syllabus and ace the exam

What happens if I don't pass the exam?

If you don't pass:

• You're allowed to retake the exam after a short waiting period
• Use the feedback report to identify areas for improvement
• Focus deeply on your weakest domains
• Practice heavily with end-to-end pipeline development

Focus. Relearn. Re-test. Persistence is key in cutting-edge AI certifications.

Where can I find more information?

Detailed documentation, registration links, and official preparation resources can be found on the official Databricks Certified Generative AI Engineer Associate exam page.

This exam overview arms you with clarity and structure — now it’s up to you to prepare, practice, and propel your generative AI career forward. Good luck!