Principal Product Manager Architect

MicrosoftRedmond, WA
7d

About The Position

Microsoft is transforming how the world works with AI and reshaping human productivity for the next generation. The Copilot ecosystem is at the center of this shift. Our team builds advanced AI agents on the Microsoft 365 and Azure AI platforms. We partner with innovative enterprise customers to incubate new platform capabilities, validate frontier agent scenarios, and accelerate adoption of modern AI architectures. We are hiring a Principal Product Manager Architect who brings deep technical skills, thought leadership, and experience with emerging AI technologies. This role is ideal for a product leader who wants to operate on the frontier of agentic AI, guide customers through advanced architectural choices, and shape the next wave of platform capabilities. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Requirements

  • Bachelor's Degree AND 8+ years experience in product/service/program management or software development OR equivalent experience.
  • Demonstrable hands-on experience building with modern AI tooling including agent frameworks, orchestration engines, retrieval pipelines, and leading LLM ecosystems.
  • Experience designing enterprise AI scenarios using Microsoft 365 Copilot extensibility, Copilot Studio, Graph Connectors, or Azure AI.
  • Technical depth in cloud architecture, distributed systems, enterprise application design, and modern AI architectural concepts.
  • Experience with conversational AI, autonomous workflows, multi-agent patterns, grounding strategies, and evaluation approaches.
  • Ability to operate in ambiguous environments, make clear decisions, and collaborate effectively across engineering, design, research, and field organizations.
  • Strong written, verbal, and visual communication skills across technical and executive audiences.
  • Ability to define metrics, use analytics, and drive data-informed product direction.
  • Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
  • Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

  • Relevant university degree in computer science, software engineering, artificial intelligence, or similar field.
  • Recent experience with generative AI architectures, agent toolchains, retrieval strategies, or competitive AI platforms.
  • Experience in rapid prototyping, incubation programs, or customer-focused innovation work.
  • Familiarity with the Microsoft technology stack including M365 extensibility patterns, Copilot Studio agent building, Azure OpenAI, and custom toolchain integration.
  • Experience influencing engineering roadmaps using customer signals and architectural insights.

Responsibilities

  • Architect the next generation of AI agents
  • Provide technical architecture guidance across agentic workflows, grounding strategies, tool integration, retrieval pipelines, multi agent patterns, and orchestration models.
  • Advise customers on optimum AI agent architectures across data surfaces, security boundaries, extensibility points, and operational requirements.
  • Partner closely with engineering teams to validate architectural patterns and influence platform capabilities.
  • Lead customer innovation and early adopter engagements
  • Drive architectural design sessions for bleeding edge agent scenarios with strategic enterprise customers.
  • Partner with Forward Deployed Engineering and Builder PM teams to validate new platform capabilities and pilot frontier agent patterns.
  • Serve as a trusted advisor in customer conversations focused on complex AI implementations.
  • Shape platform direction and ecosystem strategy
  • Track emerging AI tooling, modern agent frameworks, orchestration engines, retrieval innovations, and competitive LLM ecosystems.
  • Represent customer evidence, architectural insights, and ecosystem gaps to engineering teams to shape long term platform investments.
  • Prototype architectural frameworks, templates, and best practices that accelerate adoption across the ecosystem.
  • Influence internal and external thought leadership
  • Evangelize modern AI architectures and agent capabilities internally and externally.
  • Contribute to executive reviews, industry forums, and community engagements focused on next generation AI solutions.
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