Azure AI Engineering Deep Dive: RAG & Intelligent Agents
Build enterprise RAG solutions and intelligent AI agents using Azure AI Search, vector indexing, tool orchestration, and evaluation techniques.
Retrieval-Augmented Generation (RAG) and AI agents are transforming how organizations interact with internal knowledge and automate complex workflows. This advanced deep dive focuses on engineering enterprise-grade AI systems that combine large language models with secure data retrieval, intelligent tool usage, and automated evaluation pipelines.
Participants will learn how to design reliable RAG architectures that move beyond basic demos — including vector indexing strategies, hybrid search approaches, context optimization, and agent orchestration patterns used in production environments.
Hands-on labs guide attendees through building a knowledge-driven AI solution capable of retrieving enterprise data, invoking tools, and generating grounded responses while minimizing hallucinations and improving reliability.
Key Skills Covered
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Enterprise RAG architecture design
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Vector search and indexing strategies with Azure AI Search
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Data ingestion and chunking approaches
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Intelligent agent orchestration and tool calling
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Retrieval optimization techniques
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Evaluation and testing methodologies for AI responses
Who Should Attend
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AI engineers and developers
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Solution architects implementing knowledge-based AI systems
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Cloud engineers working with enterprise AI solutions
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Teams building internal copilots or AI assistants
Suggested Prerequisites
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Experience building AI-powered applications (see: Azure AI Engineering Deep Dive: Application Architecture)
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Understanding of REST APIs and cloud architecture fundamentals
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Familiarity with Azure services and basic AI concepts