About the Role

Microsoft seeks a Principal AI Network Architect to design ultra-high bandwidth, low-latency backend networks for next-generation GPU and AI accelerator platforms. The role involves driving system-level integration for scalable AI training workloads and collaborating with cross-functional teams and industry partners to shape hyperscale AI infrastructure.

Key Responsibilities

• Spearhead architectural definition and innovation for next-generation GPU and AI accelerator platforms
• Drive system-level integration across compute, storage, and interconnect domains
• Partner with silicon, firmware, and datacenter engineering teams to co-design infrastructure
• Cultivate deep technical relationships with silicon vendors, optics suppliers, and switch fabric providers
• Evaluate and articulate tradeoffs across electrical, mechanical, thermal, and signal integrity domains

Required Skills & Qualifications

Must Have:

• Bachelor's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, or related field AND 8+ years technical engineering experience OR Master's Degree AND 7+ years OR equivalent experience
• 5+ years of experience in designing AI backend networks and integrating them into large-scale GPU systems
• Ability to meet Microsoft, customer and/or government security screening requirements including Microsoft Cloud Background Check

Nice to Have:

• Proven expertise in system architecture across compute, networking, and accelerator domains
• Deep understanding of RDMA protocols (RoCE, InfiniBand), congestion control (DCQCN), and Layer 2/3 routing
• Experience with optical interconnects (e.g., PSM, WDM), link budget analysis, and transceiver integration
• Familiarity with signal integrity modeling, link training, and physical layer optimization
• Experience architecting backend networks for AI training and Inference workloads, including Hamiltonian cycle traffic and collective operations

Benefits & Perks

• Industry leading healthcare