Design and implement multi-agent AI solutions Skip to main Content

Exams Vouchers: Design and implement multi-agent AI solutions (AI-500)

  • Price: $83.00
  • Code: AI-500

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Description

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As a candidate for this exam, you’re an expert-level practitioner who has subject matter expertise in designing, building, and optimizing scalable, production‑ready, multi-agent AI systems and workflows. You manage the development from design to production.

 

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.

 

Updated Sept. 2026

Objectives

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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%)

Content

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Module 1: Architect production-grade multi-agent AI solutions 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 2: Build production-grade multi-agent capabilities with Microsoft Foundry

  • Design advanced prompting strategies for production AI agents
  • Build enterprise-grade tool ecosystems with MCP and Microsoft Foundry
  • Implement advanced RAG pipelines with Azure AI Search and Microsoft Foundry
  • Design multi-agent memory architectures with Azure Cosmos DB

Module 3: Deploy and govern enterprise agentic AI solutions on Azure

  • 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

  • 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

Pre-requisites

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For this exam, you should have experience developing AI and machine learning, deploying agentic systems in production environments, and orchestrating agent logic using Microsoft Foundry. You should also be proficient in Python.

Additionally, you need experience developing solutions that include Azure compute, network, storage, and data services. You should be familiar with open-source frameworks and standards, including Microsoft Agent Framework, Model Context Protocol (MCP), retrieval-augmented generation (RAG), and LangGraph.