Architect multi-agent AI systems that can move from experimentation to secure, scalable production on Azure.
Enterprise agentic AI requires more than building individual agents.
This advanced course develops the skills to design multi-agent architectures, integrate tools and data, orchestrate agent collaboration, and implement the monitoring, security, governance, and operational practices needed for production environments using Microsoft Foundry and Azure.
- Why get trained: Design, build, orchestrate, deploy, monitor, secure, and govern production-ready multi-agent AI solutions
- Why it matters: Production agentic systems require scalable architecture, reliable orchestration, observability, security, and governance beyond individual AI agents
- Who should attend: Experienced AI engineers, developers, solution architects, and practitioners building production multi-agent systems
Turn advanced AI development experience into the ability to deliver governed, production-ready agentic solutions, and prepare for the Microsoft Certified: Multi-Agent AI Solutions Expert (AI-500) certification exam. HRD Corp Claimable.
Overview
This course focuses on the practical skills needed to architect and develop multi-agent AI solutions using Microsoft Foundry and Azure, validating your ability to design logical architecture for multi-agent solutions, build and integrate tool ecosystems, implement multi-agent orchestration and integration of monitoring, security and governance.
Skills Covered
- Architect scalable and production-ready multi-agent AI solutions on Azure.
- Develop multi-agent AI applications using Microsoft Foundry and Azure.
- Build agentic workflows, tool ecosystems, and multi-agent orchestration.
- Integrate AI agents with enterprise applications, tools, and services.
- Deploy production-grade multi-agent AI solutions using Azure and CI/CD pipelines.
- Implement security, Zero Trust, governance, and responsible AI practices.
- Monitor multi-agent AI solutions using Azure Monitor, Application Insights, and OpenTelemetry.
- Evaluate AI agent performance and response quality using LLM-based evaluation techniques.
- Optimize multi-agent AI solutions for performance, scalability, and cost efficiency.
- Manage AI agent lifecycles across development, deployment, and production environments.
- Implement human-in-the-loop approval and intervention workflows.
- Analyze production issues, troubleshoot AI agents, and perform structured incident response.
Prerequisites
- Completion of AI-103: Develop AI agents on Azure or equivalent hands-on experience building and deploying agents
- Working experience with Microsoft Foundry Agent Service and Microsoft Agent Framework
- Experience consuming MCP tools and custom function tools with Microsoft Foundry Agent Service
- Familiarity with classic RAG retrieval patterns using Azure AI Search (hybrid search, semantic ranking); experience with Foundry IQ agentic retrieval is beneficial but not required
- Familiarity with foundational multi-agent orchestration patterns (sequential, concurrent, group chat, handoff)
- Basic knowledge of the A2A protocol and how to connect to a remote agent
- Python programming proficiency, including async patterns and REST API consumption
- Python proficiency with the Azure AI SDK and Azure OpenAI SDK
Target Audience
Candidates for this course, are expert-level practitioners who have subject matter expertise in designing, building, and optimizing scalable, production‑ready, multi-agent AI systems, solutions and workflows.
Out of your job role, you work closely with developers, machine learning engineers, platform engineers, data scientists, and business stakeholders to translate complex requirements into production-ready, multi-agent solutions.
Module 1: Architect production-grade multi-agent AI solutions in Azure
Production-grade multi-agent AI solutions require a deep understanding of agentic architectures, orchestration patterns, and communication strategies. This learning path will guide you through the essential concepts and best practices for building scalable and maintainable multi-agent systems in Azure.
- Design stateful agentic loops with Microsoft Foundry agent service
- Implement advanced multi-agent orchestration patterns in Microsoft Foundry
- Apply task decomposition and agent collaboration strategies in Microsoft Foundry
- Design enterprise-scale agent communication with A2A in Azure
Module 3: Deploy and govern enterprise agentic AI solutions on Azure
Deploying and governing enterprise agentic AI solutions on Azure requires a structured approach to CI/CD pipelines, zero-trust security, responsible AI compliance, and agent lifecycle management. This learning path guides you through the operational and governance capabilities required to run multi-agent systems reliably and safely at enterprise scale.
- Implement CI/CD pipelines for multi-agent systems with GitHub Actions
- Secure multi-agent systems with Azure zero-trust architecture
- Scale responsible AI governance with Azure AI Content Safety and Microsoft Foundry
- Govern the enterprise agent lifecycle in Microsoft Foundry
Module 4: Monitor, evaluate, and operate multi-agent AI solutions in Azure
Operating production-grade multi-agent AI solutions in Azure requires end-to-end visibility, systematic quality measurement, and structured incident response. This learning path guides you through distributed OpenTelemetry observability with Azure Monitor Application Insights, LLM-as-judge agent evaluation using Azure AI Foundry, multi-agent cost and performance optimization, enterprise human-in-the-loop approval workflows with Power Automate, and structured debugging procedures for production AI incidents.
- Implement distributed observability for multi-agent solutions with OpenTelemetry
- Design evaluation frameworks for multi-agent solutions with Microsoft Foundry
- Optimize multi-agent performance and cost in Microsoft Foundry
- Design human-in-the-loop approval workflows with Power Automate and Microsoft Teams
- Debug and respond to production multi-agent incidents in Azure
Certification prerequisites:
To become a Microsoft Certified: Multi-Agent AI Solutions Expert (beta), you must earn the Microsoft Certified: Azure AI Apps and Agents Developer Associate certification.
Exam & Certification
Microsoft Certified: Multi-Agent AI Solutions Expert.
As organizations move from standalone AI features to complex, multi-agent systems, the skills required are evolving fast. Organizations are no longer just experimenting, they’re deploying production-scale agent ecosystems that must be orchestrated, governed, and optimized.
Introducing the Microsoft Certified: Multi-Agent AI Solutions Expert Certification, that validates your ability to design, build, and operate scalable, production-ready multi-agent AI solutions.
Assessed on this exam
- Architect multi-agent solutions (15–20%)
- Develop multi-agent solutions in Azure (30–35%)
- Evaluate, optimize, and monitor multi-agent solutions (20–25%)
- Secure, govern, and deploy multi-agent solutions (20–25%)
Training & Certification Guide
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