Principal AI Network Hardware Systems Engineer

Experteer Overview In this role you will lead the architecture, bring-up, validation, optimization, and deployment of networking infrastructure for Microsoft’s MAIA AI platform. You will influence architectural direction and collaborate with silicon, firmware, hardware, software, and Azure teams to deliver scalable AI networking solutions at hyperscale. The position focuses on high-speed networking, AI fabric performance, and end-to-end system integration to enable next-generation AI workloads. This is a unique opportunity to shape AI networking for large-scale AI systems and infrastructure. Compensation / Benefits * Define networking requirements for large-scale AI training and inference clusters * Collaborate across silicon, system software, firmware, hardware, and Azure teams to deliver scalable networking solutions from concept to datacenter deployment * Participate in architecture reviews and influence AI networking roadmaps * Define concepts of operation, telemetry, serviceability, and operational models for AI infrastructure * Lead design and validation of IP-based AI networking (TCP/IP, UDP, routing, QoS) * Analyze transport-layer performance across distributed AI workloads * Evaluate and debug network protocol implementations impacting latency, throughput, and reliability * Drive optimization of network paths for distributed AI training and inference * Design, validate, and optimize RDMA-based networking for AI clusters * Develop validation methodologies for AI traffic patterns and workloads * Develop networking validation strategies for functionality, performance, scale, interoperability, resiliency * Characterize network behavior under AI workloads and automate stress and performance qualification * Lead end-to-end debugging across layers and implement corrective actions using fleet telemetry * Build and improve network observability, telemetry, and monitoring tooling * Improve engineering productivity through automated testing and network health assessment frameworks Tasks * 8+ years of NW HW development experience * 8+ years of GPU-based SU/SO development experience * 8+ years of hands-on HS interface architecture and development * Master’s or Bachelor’s degree in relevant field or equivalent experience * Ability to meet Microsoft security screening requirements Key requirements *

US and operational models for AI infrastructure * Lead design and validation of IP-based AI networking (TCP/IP, UDP, routing, QoS) * Analyze transport-layer performance across distributed AI workloads * Evaluate and debug network protocol implementations impacting latency, throughput, and reliability * Drive optimization of network paths for distributed AI training and inference * Design, validate, and optimize RDMA-based networking for AI clusters * Develop validation methodologies for AI traffic patterns and workloads * Develop networking validation strategies for functionality, performance, scale, interoperability, resiliency * Characterize network behavior under AI workloads and automate stress and performance qualification * Lead end-to-end debugging across layers and implement corrective actions using fleet telemetry * Build and improve network observability, telemetry, and monitoring tooling * Improve engineering productivity through automated testing and network health assessment frameworks Tasks * 8+ years of NW HW development experience * 8+ years of GPU-based SU/SO development experience * 8+ years of hands-on HS interface architecture and development * Master’s or Bachelor’s degree in relevant field or equivalent experience * Ability to meet Microsoft security screening requirements Key requirements *