| What is Microsoft Foundry and how is it used for AI application development? |
| What is Azure OpenAI and how does it support Generative AI applications? |
| What is the difference between Microsoft Foundry and Azure OpenAI? |
| What are Foundation Models and how are they used in Azure AI solutions? |
| How do you select an appropriate model for an enterprise AI application? |
| How do you deploy a model in Azure OpenAI? |
| How do you manage model versions and deployments in Azure? |
| How do you control Azure OpenAI token usage and costs? |
| How do you design a production-ready Azure OpenAI architecture? |
| How do you handle Azure OpenAI quotas and rate limits? |
| What is Generative AI and how does Azure support Generative AI development? |
| What is the difference between an LLM, SLM and Foundation Model? |
| How does inference work with Azure OpenAI models? |
| What are temperature, top-p, max tokens and seed parameters? |
| How do you control hallucinations in an Azure Generative AI application? |
| How do you handle context-window limitations in Azure OpenAI? |
| How do you generate structured JSON responses from Azure OpenAI? |
| How do you implement reusable prompt templates in Microsoft Foundry? |
| How do you evaluate the quality of an LLM response? |
| How do you design an enterprise-grade Generative AI solution on Azure? |
| What is prompt engineering? |
| What is the difference between zero-shot, one-shot and few-shot prompting? |
| How do system, user and developer instructions differ in an AI application? |
| How do you design prompts for enterprise AI applications? |
| How do you protect Azure OpenAI applications from prompt injection? |
| How do you make LLM responses more deterministic? |
| How do you create reusable and versioned prompts? |
| How do you evaluate different prompt versions? |
| How do you reduce token consumption through prompt optimization? |
| How would you troubleshoot poor LLM responses caused by prompting? |
| What is Retrieval-Augmented Generation (RAG)? |
| How do you implement RAG using Azure AI services? |
| What is Azure AI Search and why is it important for RAG? |
| How does Azure AI Search work internally in a RAG architecture? |
| How do you ingest documents into Azure AI Search? |
| How do you choose an appropriate document chunking strategy? |
| What are embeddings and how are they used in Azure RAG solutions? |
| How do you select an embedding model for Azure AI Search? |
| What is vector search and how does it differ from keyword search? |
| How do you improve retrieval accuracy in an Azure RAG application? |
| What is hybrid search in Azure AI Search? |
| How do you implement semantic ranking in Azure AI Search? |
| How do you implement metadata filtering in Azure AI Search? |
| How do you prevent irrelevant documents from being retrieved? |
| How do you evaluate RAG retrieval quality? |
| How do you troubleshoot hallucinations in an Azure RAG pipeline? |
| How do you implement citation and source grounding in RAG? |
| How do you design a scalable enterprise RAG architecture on Azure? |
| What is an AI Agent? |
| How are AI Agents different from traditional LLM applications? |
| What are the major components of an AI Agent? |
| What is Foundry Agent Service? |
| How does an Azure AI Agent perform tool calling? |
| How do you connect an AI Agent to enterprise APIs? |
| How do you implement memory for an AI Agent? |
| How do you implement multi-step workflows for AI Agents? |
| How do you design a multi-agent architecture on Azure? |
| How do you integrate MCP with Azure AI Agents? |
| How do you secure an AI Agent that can execute business operations? |
| How do you prevent an AI Agent from executing unauthorized tools? |
| How do you monitor and debug an autonomous AI Agent? |
| How do you evaluate AI Agent reliability and task completion? |
| How would you build a production-ready Agentic AI system on Azure? |
| How can Azure Functions be used as tools for AI Agents? |
| How can Azure API Management be used to expose Agent tools? |
| How can Azure Service Bus support asynchronous Agent workflows? |
| How can Azure Event Hubs support real-time AI applications? |
| How can Azure Event Grid be used in event-driven Agent architectures? |
| How do you implement retries and failure handling in Agent workflows? |
| What is Azure Machine Learning and when should it be used? |
| When would you choose Azure Machine Learning instead of Azure OpenAI? |
| How do you train a custom machine learning model using Azure Machine Learning? |
| How do you fine-tune AI models on Azure? |
| How do you deploy ML models using managed online endpoints? |
| What is batch inference and when would you use it? |
| How do you implement MLOps using Azure Machine Learning? |
| How do you monitor machine learning models in production? |
| How is Azure Blob Storage used in AI and RAG architectures? |
| How is Azure Data Lake Storage Gen2 used for AI data engineering? |
| How is Azure AI Document Intelligence used in an enterprise RAG pipeline? |
| How do you extract structured information from PDFs using Azure AI services? |
| How do Cosmos DB and PostgreSQL support AI application data? |
| How do you implement Agent memory using Azure Cosmos DB? |
| How do you secure Azure OpenAI using Microsoft Entra ID? |
| How do Managed Identities improve security in Azure AI applications? |
| How do you use Azure Key Vault to protect AI application secrets? |
| How do you implement network isolation for an enterprise Azure AI application? |
| How do you protect AI applications against data leakage and prompt injection? |
| How does Azure AI Content Safety protect Generative AI applications? |
| How do you implement responsible AI controls in Azure? |
| How do you monitor Azure OpenAI applications using Azure Monitor? |
| How do you trace AI application requests using Application Insights? |
| What metrics should be monitored for a production RAG application? |
| How do you monitor LLM latency, token usage and AI application cost? |
| How do you troubleshoot a production AI application using Azure Monitor and Application Insights? |
| How would you design an enterprise RAG application using Azure OpenAI, AI Search and Blob Storage? |
| How would you design a scalable Agentic AI platform using Microsoft Foundry? |
| How would you build a secure multi-tenant Generative AI application on Azure? |
| How would you design an AI application capable of handling millions of requests? |
| How would you reduce the cost of a production Azure Generative AI application? |
| How would you integrate a Java Spring Boot application with Azure OpenAI? |
| How would you integrate Kafka or Azure Event Hubs with an AI Agent architecture? |
| How would you design an end-to-end Agentic RAG solution using Azure OpenAI, AI Search, Functions and Cosmos DB? |
| How would you implement CI/CD for an Azure AI application? |
| How would you design a production-grade Azure Agentic AI platform with security, observability, scalability and governance? |
