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Exam Code: Databricks-Generative-AI-Engineer-Associate
Exam Title: Databricks Certified Generative AI Engineer Associate
Vendor: Databricks
Exam Questions: 61
Last Updated: March 9th,2026

Question 1

A Generative AI Engineer has a provisioned throughput model serving endpoint as part of a RAG application and would like to monitor the serving endpoint??s incoming requests and outgoing responses. The current approach is to include a micro-service in between the endpoint and the user interface to write logs to a remote server.
Which Databricks feature should they use instead which will perform the same task?

A. Vector Search
B. Lakeview
C. DBSQL
D. Inference Tables

Correct Answer:D

Question 2

A Generative AI Engineer is designing a RAG application for answering user questions on technical regulations as they learn a new sport.
What are the steps needed to build this RAG application and deploy it?

A. Ingest documents from a source –> Index the documents and saves to Vector Search–> User submits queries against an LLM –> LLM retrieves relevant documents –> Evaluate model –> LLM generates a response –> Deploy it using Model Serving
B. Ingest documents from a source –> Index the documents and save to Vector Search –> User submits queries against an LLM –> LLM retrieves relevant documents –> LLM generates a response -> Evaluate model –> Deploy it using Model Serving
C. Ingest documents from a source –> Index the documents and save to Vector Search –> Evaluate model –> Deploy it using Model Serving
D. User submits queries against an LLM –> Ingest documents from a source –> Index the documents and save to Vector Search –> LLM retrieves relevant documents –> LLM generates a response –> Evaluate model –> Deploy it using Model Serving

Correct Answer:B

Question 3

When developing an LLM application, it??s crucial to ensure that the data used for training the model complies with licensing requirements to avoid legal risks.
Which action is NOT appropriate to avoid legal risks?

A. Reach out to the data curators directly before you have started using the trained model to let them know.
B. Use any available data you personally created which is completely original and you can decide what license to use.
C. Only use data explicitly labeled with an open license and ensure the license terms are followed.
D. Reach out to the data curators directly after you have started using the trained model to let them know.

Correct Answer:D

Question 4

A Generative Al Engineer is tasked with improving the RAG quality by addressing its inflammatory outputs.
Which action would be most effective in mitigating the problem of offensive text outputs?

A. Increase the frequency of upstream data updates
B. Inform the user of the expected RAG behavior
C. Restrict access to the data sources to a limited number of users
D. Curate upstream data properly that includes manual review before it is fed into the RAG system

Correct Answer:D

Question 5

A Generative Al Engineer is tasked with developing a RAG application that will help a small internal group of experts at their company answer specific questions, augmented by an internal knowledge base. They want the best possible quality in the answers, and neither latency nor throughput is a huge concern given that the user group is small and they??re willing to wait for the best answer. The topics are sensitive in nature and the data is highly confidential and so, due to regulatory requirements, none of the information is allowed to be transmitted to third parties.
Which model meets all the Generative Al Engineer??s needs in this situation?

A. Dolly 1.5B
B. OpenAI GPT-4
C. BGE-large
D. Llama2-70B

Correct Answer:C