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Principal AI Systems Architect

Microsoft· Hardware Engineering
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Redmond, WA, Mountain View, CA$165.6k - $296.4kFull-timePosted 4w ago

About the role

Lead the system architecture for AI accelerator systems within Microsoft Azure Hardware Systems and Infrastructure, owning architecture requirements and influencing cross-functional teams to de-risk and implement AI rack- and cluster-scale solutions.

Responsibilities

  • Define AI rack- and cluster-scale architecture across accelerator, host, network, memory, storage, power, cooling, and datacenter constraints. Make quantitative tradeoffs across performance and TCO.
  • Develop functional proof-of-concepts to evaluate and de-risk new capabilities
  • Write and own high-level product requirements and specifications
  • Drive alignment across cross-functional engineering and leadership teams. Own the outcomes.
  • Use performance simulations and hardware models for what-if studies to evaluate and choose between architecture options.
  • Industry influence: Participate in industry consortiums to shape standards, and influence vendor roadmaps.

Qualifications

  • Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 9+ years technical engineering experience OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 11+ years technical engineering experience OR equivalent experience
  • Doctorate in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 8+ years technical engineering experience OR Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 12+ years technical engineering experience OR Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 15+ years technical engineering experience OR equivalent experience
  • Experience in large scale AI datacenter systems and their network
  • Demonstrated expertise in one or more of these domains: networking (RoCE, Infiniband transports, congestion control, network topology design), reliability and serviceability, datacenter architecture for large scale AI systems
  • Experience owning hardware system architecture at scale – machine, rack row and cluster, authoring specifications and requirements
  • Ability to make decision trade-offs across domains
  • Deep expertise in AI systems or a key domain such as networking, reliability, power management
  • Skilled in partnering and influencing architects, hardware engineers, and software leads
  • Ability to manage through ambiguity, bringing clarity to establish direction and driving decisions
  • Collaboration skills, teamwork, and sense of presumed responsibility

Skills

Required:AI rack- and cluster-scale architecturePerformance simulations and hardware modelingCross-functional leadership and collaboration
Last updated Oct 1, 2026. Interested? Apply on the company site.

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