Data Engineers in Toronto September 2026 Semimonthly Meeting
Topic: Building Collaborative AI Agents Using AI Foundry Agent Service
Abstract:
As enterprise AI adoption grows, many real-world scenarios can no longer be solved by a single conversational agent. Instead, they require multiple specialized agents that collaborate, share context, and delegate responsibilities intelligently. This session focuses on how to design and implement multi-agent architectures using Azure AI Foundry’s Agent Service.
We’ll start by breaking down when and why multi-agent systems make sense, then walk through a practical scenario where agents are assigned clear roles such as data retrieval, reasoning, and action execution. Using AI Foundry Agent Service, you’ll see how these agents are created, connected, and orchestrated to work together while maintaining context and control.
Rather than focusing on theory, the session emphasizes practical design patterns, architecture decisions, and implementation considerations, including agent boundaries, communication flows, and scaling agent-based solutions safely in enterprise environments.
By the end of the session, attendees will have a solid understanding of how to move from a single-agent approach to a collaborative, multi-agent model and how to apply these patterns using AI Foundry in their own solutions.
Key Takeaways:
\- Understand when multi\-agent architectures are the right choice
\- Learn how to design role\-based agents using AI Foundry Agent Service
\- Explore real\-world coordination and orchestration patterns
\- Gain practical guidance for scaling and governing multi\-agent systems
\- Leave with a reusable architecture blueprint for enterprise AI agents
Speaker: Mitul Tailor, Snr. Data & AI Engineer
Speaker Profile:
am a Senior Data & AI Engineer at Long View Systems, specializing in Azure services, data engineering, and AI-driven solutions. With expertise in Azure Data Factory, Fabric, Copilot Studio, and data migration,