GENERATIVE-AI-ENGINEER-ASSOCIATE Practice Questions
101 real GENERATIVE-AI-ENGINEER-ASSOCIATE exam questions with expert-verified answers and explanations. Page 2 of 3.
- Question #52MLOps and Model Governance on Databricks
A Generative AI Engineer wants their finetuned LLMs in their prod Databricks workspace available for testing in their dev workspace as well. All of their workspaces are Unity Catal...
Databricks Unity CatalogMLflow Model RegistryModel SharingAccess Control - Question #53Foundation Model Management and Operationalization
A Generative AI Engineer who was prototyping an LLM system accidentally ran thousands of inference queries against a Foundation Model endpoint over the weekend. They want to take a...
Rate LimitingFoundation ModelsAPI ManagementCost Optimization - Question #54LLM Application Security
A Generative AI Engineer is developing an LLM application to interact with users to provide personalized movie recommendations. Given the potential for malicious user inputs, which...
LLM SecuritySafety FiltersInput ValidationPrompt Guardrails - Question #55AI System Safety and Responsible AI Development
A Generative AI Engineer is building a system that will answer questions on currently unfolding news topics. As such, it pulls information from a variety of sources including artic...
AI SafetyGuardrailsContent ModerationInput Filtering - Question #56AI/ML Model Security
A Generative AI Engineer is deploying a customer-facing, fine-tuned LLM on their public website. Given the large investment the company put into fine tuning this model, and the pro...
AI SecurityModel Inversion AttacksAccess ControlDatabricks Security - Question #57Monitoring and Operationalizing LLM Applications
A Generative AI Engineer just deployed an LLM application at a digital marketing company that assists with answering customer service inquiries. Which metric should they monitor fo...
LLM application monitoringProduction metricsDeploymentOperational metrics - Question #58Model Deployment and Monitoring
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 out...
Databricks Model ServingMLOps MonitoringInference Logging - Question #59Responsible AI
Which indicator should be considered to evaluate the safety of the LLM outputs when qualitatively assessing LLM responses for a translation use case?
LLM EvaluationModel SafetyTranslation QualityQualitative Assessment - Question #60Evaluating RAG Systems for Improvement
A Generative AI Engineer has created a RAG application which can help employees retrieve answers from an internal knowledge base, such as Confluence pages or Google Drive. The prot...
RAG System EvaluationComponent-wise EvaluationSystem DiagnosticsGenerative AI Engineering - Question #61Designing Generative AI Applications for User Engagement
A Generative AI Engineer is designing a chatbot for a gaming company that aims to engage users on its platform while its users play online video games. Which metric would help them...
Chatbot designUser engagementGenerative AI applicationsUser experience (UX) - Question #62MLOps
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 out...
Model ServingInference LoggingMonitoringDatabricks - Question #63LLM Evaluation Metrics
A Generative AI Engineer has built an LLM-based system that will automatically translate user text between two languages. They now want to benchmark multiple LLM's on this task and...
LLM EvaluationMachine TranslationNLP MetricsBLEU Score - Question #64RAG System Evaluation
A Generative AI Engineer has created a RAG application which can help employees interpret HR documentation. The prototype application is now working with some positive feedback fro...
RAG EvaluationSystem PerformanceDiagnostic TestingGenerative AI Applications - Question #65Building and Optimizing RAG Pipelines
A team uses Mosaic AI Vector Search to retrieve documents for their Retrieval-Augmented Generation (RAG) pipeline. The search query returns five relevant documents, and the first t...
RAGVector SearchDocument RerankingContext Optimization - Question #66AI Agent Deployment and Monitoring
A generative AI engineer is deploying an AI agent authored with MLflow's ChatAgent interface for a retail company's customer support system on Databricks. The agent must handle tho...
AI Agent DeploymentMLOpsMonitoringOperational Metrics - Question #67Data Management and Optimization in Databricks Lakehouse
Which steps are essential when writing chunked text into Delta Lake tables in Unity Catalog? (Choose two.)
Delta LakeData PartitioningData StructuringQuery Optimization - Question #68Vector Database Management
A Generative AI Engineer is loading 150 million embeddings into a vector database that takes a maximum of 100 million. Which TWO actions can they take to reduce the record count?
Vector DatabasesText ChunkingEmbeddingsData Preprocessing - Question #69Natural Language Processing (NLP) with LLMs
A Generative AI Engineer would like to build an application that can update a memo field that is about a paragraph long to just a single sentence gist that shows intent of the memo...
SummarizationNatural Language Processing (NLP)LLM ApplicationsText Generation - Question #70LLM Application Development and Optimization
A Generative AI Engineer is creating a LLM-based application. The documents for its retriever have been chunked to a maximum of 512 tokens each. The Generative AI Engineer knows th...
RAG System DesignLLM Performance OptimizationCost-Latency TradeoffsContext Window Management - Question #71Real-time Data Serving for LLM Applications
A Generative AI Engineer is designing an LLM-powered live sports commentary platform. The platform provides real-time updates and LLM-generated analyses for any users who would lik...
Feature ServingReal-time DataLLM ApplicationsMLOps - Question #72Prompt Engineering
A Generative AI Engineer interfaces with an LLM with prompt/response behavior that has been trained on customer calls inquiring about product availability. The LLM is designed to o...
Prompt EngineeringLLM InteractionSystem PromptsText Classification - Question #73Generative AI Application Architecture
A Generative AI Engineer has been asked to design an LLM-based application that accomplishes the following business objective: answer employee HR questions using HR PDF documentati...
Retrieval Augmented Generation (RAG)Vector StoresDocument ChunkingEmbeddings - Question #74LLM Agent System Design
A Generative AI Engineer is creating an agent-based LLM system for their favorite monster truck team. The system can answer text based questions about the monster truck team, looku...
LLM AgentsTool UseSystem PromptingGenerative AI Architecture - Question #75Generative AI Application Design
A Generative AI Engineer wants to build an LLM-based solution to help a restaurant improve its online customer experience with bookings by automatically handling common customer in...
LLM Application DesignConversational AIInput/Output DefinitionCustomer Service Automation - Question #76LLM Application Architecture
A Generative AI Engineer is creating an LLM-powered application that will need access to up-to- date news articles and stock prices. The design requires the use of stock prices whi...
LLM AgentsTool UseExternal Data IntegrationDelta Lake - Question #77RAG System Architecture
A company has a typical RAG-enabled, customer-facing chatbot on its website. Select the correct sequence of components a user's questions will go through before the final output is...
RAGLLM ArchitectureVector SearchEmbedding Models - Question #78Generative AI Model Capabilities and Selection
A Generative AI Engineer is building an LLM-based application that has an important transcription (speech-to-text) task. Speed is essential for the success of the application. Whic...
Speech-to-TextWhisper ModelModel SelectionGenerative AI Applications - Question #79Generative AI Model Selection
A Generative AI Engineer is asked to build an LLM application that would excel at code generation. They need to select a model that has been specifically trained to generate code....
Large Language ModelsCode GenerationModel SelectionCodeLlama - Question #80LLM Agent Design
A Generative AI Engineer needs to design an LLM pipeline to conduct multi-stage reasoning that leverages external tools. To be effective at this, the LLM will need to plan and adap...
LLM AgentsTool UseReAct FrameworkMulti-stage Reasoning - Question #81LLM Application Design
A Generative AI Engineer at a home appliance company has been asked to design an LLM based application that accomplishes the following business objective: answer customer questions...
Retrieval Augmented Generation (RAG)Vector StoresEmbeddingsInformation Retrieval - Question #82Data Ingestion and Preprocessing for Generative AI
A Generative AI Engineer is building a RAG application that will rely on context retrieved from source documents that have been scanned and saved as image files in formats like .jp...
OCRPython LibrariesRAG Data SourcesImage Text Extraction - Question #83Prompt Engineering Best Practices
Which of the following are essential components when designing a prompt for a Generative AI model? (Choose two.)
Prompt engineeringPrompt designGenerative AI interactionPrompt best practices - Question #84Prompt Engineering
Which of the following strategies would best help in designing a prompt that leads to a well- formatted response in an LLM? (Choose two.)
Prompt EngineeringLLM Output FormattingPrompt DesignGenerative AI Best Practices - Question #85Building Retrieval-Augmented Generation (RAG) Applications
Which of the following are key considerations when identifying source documents for a RAG application? (Choose two.)
RAGData PreparationInformation RetrievalSource Document Selection - Question #86Generative AI Application Design
A Generative AI Engineer is responsible for developing a chatbot to enable their company's internal HelpDesk Call Center team to more quickly find related tickets and provide resol...
Data Source SelectionGenerative AI Application DesignContextual Information Retrieval - Question #87RAG Application Optimization
Generative AI Engineer at an electronics company just deployed a RAG application for customers to ask questions about products that the company carries. However, they received feed...
RAGRetrieval QualityRelevanceTroubleshooting - Question #88Vector Store Management and Indexing on Databricks
A Generative AI Engineer using the code below to test setting up a vector store: Assuming they intend to use Databricks managed embeddings with the default embedding model, what sh...
Databricks Vector SearchVector Store CreationManaged EmbeddingsDelta Lake Integration - Question #89RAG Pipeline Design and Optimization
After changing the response generating LLM in a RAG pipeline from GPT-4 to a model with a shorter context length that the company self-hosts, the Generative AI Engineer is getting...
RAG PipelinesLLM Context WindowVector SearchPrompt Engineering - Question #90Building and Optimizing RAG Applications
A Generative AI Engineer is building a RAG application that answers questions about internal documents for the company SnoPen AI. The source documents may contain a significant amo...
RAG ApplicationsPrompt EngineeringInformation FilteringLLM Behavior Control - Question #91Data Ingestion and Preparation for Vector Search
A Generative AI Engineer has successfully ingested unstructured documents and chunked them by document sections. They would like to store the chunks in a Vector Search index. The c...
Data PreprocessingVector Search IndexingRAG ArchitectureDatabricks Data Engineering - Question #92Data Ingestion for RAG
A Generative AI Engineer is building a RAG application that will rely on context retrieved from source documents that are currently in PDF format. These PDFs can contain both text...
RAG ApplicationsDocument ParsingText ExtractionPython Libraries - Question #93Building and Optimizing RAG Applications
A Generative AI Engineer is assessing the responses from a customer-facing GenAI application that they are developing to assist in selling automotive parts. The application require...
Retrieval Augmented Generation (RAG)Feature StoresData RetrievalGenAI Application Design - Question #94Prompt Engineering Fundamentals
Which of the following is the most effective way to design a prompt that elicits a specific format in the response?
Prompt EngineeringPrompt DesignLLM InteractionGenerative AI Best Practices - Question #95RAG System Design
A Generative AI Engineer is creating an LLM-based application. The documents for its retriever have been chunked to a maximum of 512 tokens each. The Generative AI Engineer knows t...
RAG System DesignLLM Context ManagementCost-Performance TradeoffsEmbedding Models - Question #96ML Model Deployment and MLOps
A Generative AI Engineer is tasked with deploying an application that takes advantage of a custom MLflow Pyfunc model to return some interim results. How should they configure the...
MLflow Model DeploymentSecrets ManagementEnvironment VariablesEndpoint Configuration - Question #97Model Deployment and MLOps on Databricks
A Generative AI Engineer has already trained an LLM on Databricks and it is now ready to be deployed. Which of the following steps correctly outlines the easiest process for deploy...
MLflow Model DeploymentUnity CatalogDatabricks MLOpsLLM Deployment - Question #98LLM Deployment and Cost Management
A Generative AI Engineer developed an LLM application using the provisioned throughput Foundation Model API. Now that the application is ready to be deployed, they realize their vo...
LLM DeploymentCost OptimizationFoundation ModelsAPI Throughput - Question #99LLM Application Security
A Generative AI Engineer is ready to deploy an LLM application written using Foundation Model APIs. They want to follow security best practices for production scenarios. Which auth...
AuthenticationSecurity Best PracticesApplication DeploymentOAuth - Question #100Building RAG Applications
A Generative AI Engineer is building a RAG application for answering employee questions on company policies. What are the steps needed to build this RAG application and deploy it?
RAG ArchitectureVector SearchData IngestionLLM Applications - Question #101LLM Production Deployment and Scaling
A Generative AI Engineer developed an LLM application using the pay-per-token Foundation Model API. Now that the application is ready to be deployed, they would like to ensure the...
LLM DeploymentProduction ScalingFoundation ModelsProvisioned Throughput