Microsoft Principal AI Network Architect 

Taiwan, Taoyuan City 

705778671

a trustedengineers to help achieve that mission.

the ability to deploy new offerings and hardware infrastructure on time, in high volume with high quality and lowest cost is of paramount importance. To achieve this goal,Systems Engineering (CHSE)and industry knowledge to envision and implement future technical solutions that will manage andthe Cloud infrastructure.

Required Qualifications

• Bachelor's Degree 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 7+ years technical engineering experience
  • OR equivalent experience
• 5+ years of experience in designing AI backend networks and integrating them into large-scale GPU systems.

Other Requirements:

to meet Microsoft, customer and/or government security screening requirementsrequired for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will beto pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• Proven expertise in system architecture acrosscompute, 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 trainingand Inferenceworkloads, including Hamiltonian cycle traffic and collective operations (e.g., all-reduce, all-gather).
• Hands-on design of high-radix switches (≥400Gbps per port), orthogonal chassis, andcabledbackplanes.
• Knowledge of chip-to-chip and chip-to-module interfaces, including error correction and equalization techniques.
• Experience with custom NIC IPs and transport layers for secure, reliable packet delivery.
• Familiarity with AI model execution pipelines and their impact on pod-level network design and latency SLAs.
• Prior contributions to hyperscale deployments or cloud-scale AI infrastructure programs.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until September 7, 2025.

• Technology LeadershipSpearhead architectural definition and innovation for next-generation GPU and AI accelerator platforms, with a focus on ultra-high bandwidth, low-latency backend networks. Drive system-levelintegration across compute, storage, and interconnect domains to support scalable AI training workloads.

• Technology Partnerships

• Architectural ClarityEvaluate and articulate tradeoffs across electrical, mechanical, thermal, and signal integrity domains. Frame decisions in terms of TCO, performance, scalability, and deployment risk. Lead design reviews and contribute to PRDs and system specifications.

• Industry InfluenceShape the direction of hyperscale AI infrastructure by engaging with standards bodies (e.g., IEEE 802.3), influencingcomponentroadmaps, and driving adoption of novel interconnect protocols and topologies.