GENERATIVE-AI-ENGINEER-ASSOCIATE Practice Questions
101 real GENERATIVE-AI-ENGINEER-ASSOCIATE exam questions with expert-verified answers and explanations. Page 1 of 3.
- Question #1Prompt Engineering
A Generative AI Engineer has been reviewing issues with their company's LLM based question- answering assistant and has determined that a technique called prompt chaining could hel...
Prompt ChainingPrompt EngineeringLLM TechniquesTask Decomposition - Question #2Generative AI Model Selection and Evaluation
An AI developer team wants to fine tune an open-weight model to have exceptional performance on a code generation use case. They are trying to choose the best model to start with....
Model SelectionLLM EvaluationCode GenerationCost Optimization - Question #3Generative AI Solution Design and Optimization
A small and cost-conscious startup in the cancer research field wants to build a RAG application using Foundation Model APIs. Which strategy would allow the startup to build a good...
RAGLLM SelectionCost OptimizationDomain Specificity - Question #4Vector Search Performance Evaluation
A Generative AI Engineer is deciding between using LSH (Locality Sensitive Hashing) and HNSW (Hierarchical Navigable Small World) for indexing their vector database. Their top prio...
Vector DatabasesApproximate Nearest Neighbor (ANN)Evaluation MetricsSemantic Search - Question #5Data Preparation for RAG and Vector Search
A Generative AI Engineer has written scalable PySpark code to ingest unstructured PDF documents and chunk them in preparation for storing in a Databricks Vector Search index. Curre...
PySpark Data TransformationVector Search IndexingRAG Data PreparationData Modeling - Question #6RAG System Design and Optimization
A Generative AI Engineer is developing a RAG system for their company to perform internal document Q&A for structured HR policies, but the answers returned are frequently incomplet...
RAG OptimizationContext RetrievalText ChunkingLLM Fine-tuning - Question #7Designing and Optimizing RAG Applications
A Generative AI Engineer is developing a RAG application and would like to experiment with different embedding models to improve the application performance. Which strategy for pic...
RAGEmbedding ModelsModel SelectionDomain Specificity - Question #8Designing and Implementing RAG Applications with Structured Data on Databricks
Generative AI Engineer is helping a cinema extend its website's chat bot to be able to respond to questions about specific showtimes for movies currently playing at their local the...
RAGFeature StoreReal-time Data ServingStructured Data Retrieval - Question #9LLM Model Selection
Generative AI Engineer needs to build an LLM application that can understand medical documents, including recently published ones. They want to select an open model available on Hu...
LLM SelectionDomain-specific LLMsHuggingFace HubTraining Data - Question #10RAG System Design
Generative AI Engineer is building a RAG application that answers questions about technology- related news articles. The source documents may contain a significant amount of irrele...
RAGData FilteringDocument PreprocessingInformation Retrieval - Question #11Data Ingestion and Preprocessing for Retrieval Augmented Generation (RAG)
A Generative AI Engineer is building a RAG application that will rely on context retrieved from source documents that are currently in HTML format. They want to develop a solution...
HTML ParsingText ExtractionPython LibrariesRAG Data Preparation - Question #12Vector Search Indexing and Retrieval
A Generative AI Engineer is setting up a Databricks Vector Search that will lookup news articles by topic within 10 days of the date specified. An example query might be "Tell me a...
Vector SearchMetadata FilteringInformation RetrievalDatabricks Vector Search - Question #13Generative AI Application Development
A Generative AI Engineer at an automotive company would like to build a question-answering chatbot to help customers answer specific questions about their vehicles. They have: - A...
RAG ArchitectureRAG OptimizationEmbedding ModelsPrompt Engineering - Question #14RAG Data Processing and Chunking
A Generative AI Engineer at a legal firm is designing a RAG system to analyze historical legal case precedents. The system needs to process millions of court opinions and legal doc...
RAGText ChunkingContext PreservationTemporal Data Processing - Question #15RAG System Optimization and Evaluation
A Generative AI Engineer has created a RAG application to look up answers to questions about a series of fantasy novels that are being asked on the author's web forum. The fantasy...
RAG OptimizationChunkingEvaluation MetricsLLM-as-a-Judge - Question #16Generative AI System Architecture
A Generative AI Engineer is building a Generative AI system that suggests the best matched employee team member to newly scoped projects. The team member is selected from a very la...
RAGVector DatabasesEmbeddingsSystem Architecture - Question #17Generative AI Application Development
What is the most suitable library for building a multi-step LLM-based workflow?
LLM WorkflowsLangChainGenerative AI FrameworksApplication Orchestration - Question #19Optimizing LLM Prompts for Desired Output
A Generative AI Engineer is creating an LLM system that will retrieve news articles from the year 1918 and related to a user's query and summarize them. The engineer has noticed th...
Prompt EngineeringLLM Output ControlGenerative AI Application - Question #20Prompt Engineering
A Generative AI Engineer would like an LLM to generate formatted JSON from emails. This will require parsing and extracting the following information: order ID, date, and sender em...
Prompt EngineeringInformation ExtractionStructured Data GenerationLLM Application - Question #21LLM Application Design
A Generative AI Engineer has been asked to build an LLM-based question-answering application. The application should take into account new documents that are frequently published....
RAGLLM ArchitecturesCost OptimizationQuestion Answering - Question #22Generative AI MLOps
What is an effective method to preprocess prompts using custom code before sending them to an LLM?
Prompt EngineeringMLOpsMLflowLLM Application Development - Question #23LLM Output Control
A Generative AI Engineer is building an LLM to generate article summaries in the form of a type of poem, such as a haiku, given the article content. However, the initial output fro...
Prompt EngineeringLLM Fine-tuningLLM Output ControlGenerative AI Applications - Question #24Generative AI Model Selection and Application
A team wants to serve a code generation model as an assistant for their software developers. It should support multiple programming languages. Quality is the primary objective. Whi...
Generative AI ModelsCode GenerationModel SelectionDatabricks Foundation Models - Question #25Building Generative AI Applications
A Generative AI Engineer received the following business requirements for an external chatbot. The chatbot needs to know what types of questions the user asks and routes to appropr...
LLM WorkflowChatbot ArchitectureIntent ClassificationGenerative AI Applications - Question #26LLM Model Selection and Capabilities
A Generative AI Engineer is tasked with developing an application that is based on an open source large language model (LLM). They need a foundation LLM with a large context window...
Large Language Models (LLMs)Context WindowOpen Source LLMsFoundation Models - Question #27Prompt Engineering
A Generative AI Engineer interfaces with an LLM with instruction-following capabilities trained on customer calls inquiring about product availability. The LLM should output "Succe...
Prompt EngineeringLLM InteractionText ClassificationInstruction Following - Question #28LLM Application Development and Orchestration
Which TWO chain components are required for building a basic LLM-enabled chat application that includes conversational capabilities, knowledge retrieval, and contextual memory? (Ch...
LLM Application ComponentsConversational MemoryRetrieval Augmented Generation (RAG)Chatbot Architecture - Question #29Retrieval Augmented Generation (RAG) Architecture
A Generative AI Engineer at an automotive company would like to build a question-answering chatbot for customers to inquire about their vehicles. They have a database containing va...
RAG architectureChatbot componentsEmbedding modelsVector databases - Question #30LLM Customization and Control
A Generative AI Engineer is building an LLM to generate article headlines given the article content. However, the initial output from the LLM does not match the desired tone or sty...
LLM ControlPrompt EngineeringFine-tuningOutput Post-processing - Question #31LLM Application Design and Prompt Engineering
A Generative AI Engineer is creating a customer support bot that should respond differently to an end user based on the sentiment in their initial message. For example, if the end...
Prompt EngineeringLLM ChainingSentiment AnalysisGenerative AI Architecture - Question #32Prompt Engineering for LLM Applications
A Generative AI Engineer would like an LLM to parse and extract the following information: date, sender email, and order ID. The output should be formatted into JSON. Here's an ema...
Prompt EngineeringInformation ExtractionStructured OutputLLM Applications - Question #33Prompt Engineering
A Generative AI Engineer is using an LLM to classify species of edible mushrooms based on text descriptions of certain features. The model is returning accurate responses in testin...
Prompt EngineeringLLM Output ControlSystem PromptFew-shot Prompting - Question #34Generative AI Application Design
A Generative AI Engineer is working with a retail company that wants to enhance its customer experience by automatically handling common customer inquiries. They are working on an...
LLM Use CasesCustomer Service AutomationGenerative AI ApplicationsLLM Task Definition - Question #35LLM Application Architecture and Workflow Design
A Generative AI Engineer received the following business requirements for an internal chatbot. The internal chatbot needs to know what types of questions the user asks and route th...
Chatbot ArchitectureLLM Workflow OrchestrationIntent ClassificationRetrieval Augmented Generation (RAG) - Question #36Generative AI Application Development
A Generative AI Engineer is using LangChain to assist a museum in classifying documents and using this code: Their code results in an error. What do they need to change in order to...
LangChainPrompt EngineeringPromptTemplateGenAI Application Development - Question #37Debugging Generative AI Agents
A Generative AI Engineer is developing an agent system using a popular agent-authoring library. The agent comprises multiple parallel and sequential chains. The engineer encounters...
Generative AI AgentsDebuggingStructured LoggingAgent Orchestration - Question #38Configuring and Debugging LLM Agents
A Generative AI Engineer is experimenting with using parameters to configure an agent in Mosaic Agent Framework. However, they are struggling to get the agent to respond with relev...
Prompt EngineeringLLM AgentsAgent ConfigurationParameter Handling - Question #39Building Generative AI Agents
A Generative AI Engineer is using LangGraph to define multiple tools in a single agentic application. They want to enable the main orchestrator LLM to decide on its own which tools...
LangGraphAgentic AILLM ToolsReAct - Question #40Building and Deploying RAG Applications
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...
RAG ArchitectureVector SearchData IngestionLLM Applications - Question #41Interacting with Databricks Foundation Model Endpoints
All of the following are python APIs used to query Databricks foundation models. When running in an interactive notebook, which of the following libraries does not automatically us...
Databricks APIsAuthenticationFoundation ModelsPython Libraries - Question #42RAG System Quality and Safety
A Generative AI Engineer is tasked with improving the RAG quality by addressing its inflammatory outputs. Which action would be most effective in mitigating the problem of offensiv...
RAG QualityData CurationResponsible AIContent Moderation - Question #43Responsible AI Development
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...
Data LicensingLegal ComplianceLLM Data SourcingResponsible AI - Question #44LLM Security and Safety
A Generative AI Engineer has developed an LLM application to answer questions about internal company policies. The Generative AI Engineer must ensure that the application doesn't h...
LLM SafetyData Leakage PreventionHallucination MitigationFine-tuning - Question #45LLM Application Design and Model Selection
A Generative AI 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 in...
LLM Model SelectionRAG ApplicationsData PrivacyOn-premise Deployment - Question #46Responsible AI Governance
A Generative AI Engineer is developing a chatbot designed to assist users with insurance-related queries. The chatbot is built on a large language model (LLM) and is conversational...
LLM GuardrailsResponsible AIComplianceChatbot Development - Question #47LLM Application Security and Safety
A Generative AI Engineer is developing an LLM application that users can use to generate personalized birthday poems based on their names. Which technique would be most effective i...
LLM SafetySecurity Best PracticesInput ModerationHarmful Content - Question #48AI Safety and Responsible Deployment
A Generative AI Engineer is developing a patient-facing healthcare-focused chatbot. If the patient's question is not a medical emergency, the chatbot should solicit more informatio...
AI SafetyHealthcare AIChatbot DesignEmergency Response Protocols - Question #49Ensuring Generative AI Output Quality and Safety
A Generative AI Engineer is building a system which will answer questions on latest stock news articles. Which will NOT help with ensuring the outputs are relevant to financial new...
Generative AI Output QualityAI GuardrailsSystem PerformanceContent Filtering - Question #50Data Governance for LLMs
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 most...
Data LicensingLegal ComplianceLLM Data Management - Question #51Implementing LLM Application Safety and Moderation
A Generative AI Engineer is building a production-ready LLM system which replies directly to customers. The solution makes use of the Foundation Model API via provisioned throughpu...
LLM SafetyContent ModerationProduction LLM SystemsResponsible AI