Designing real-world AI applications requires more than calling a model API. This advanced engineering deep dive teaches cloud professionals how to build production-ready AI-powered applications on Azure using modern architecture patterns, structured outputs, memory management, and responsible AI guardrails.

Participants will explore how enterprise teams design scalable AI systems that integrate with existing services, handle real-world edge cases, and deliver predictable, secure outcomes. The class emphasizes engineering discipline — including prompt design as system architecture, state management strategies, and building reliable AI service layers that move beyond proof-of-concept implementations.

Through hands-on labs led by an expert instructor, attendees will build a fully functional AI application architecture using Azure OpenAI and related Azure services, implementing best practices used by production teams.

Key Skills Covered

• Modern Azure AI application architecture patterns

• Designing reliable AI service layers

• Structured outputs and tool-enabled workflows

• Managing AI memory and conversational state

• Safety, governance, and guardrail implementation

• Cost and performance considerations for production workloads

Who Should Attend

• Cloud engineers

• Application developers

• Solution architects

• Technical leads building AI-enabled solutions

Suggested Prerequisites

• Experience with Azure fundamentals and core services

• Familiarity with APIs and application development

• General understanding of generative AI concepts (AI-900 level or equivalent helpful but not required)