About the Role

Principal Network Architect responsible for end-to-end network architecture for AI training/inference clusters at Microsoft. Leads a team of engineers to design, optimize, and validate large-scale network fabrics for hyperscale cloud infrastructure.

Key Responsibilities

• Own end-to-end network architecture for AI training/inference clusters
• Lead and grow a high-performing team of engineers
• Define scale-out/scale-up designs and network services
• Drive congestion-control strategy and transport tuning
• Evaluate and influence silicon & optics roadmaps

Required Skills & Qualifications

Must Have:

• Master's Degree in Electrical Engineering, Computer Engineering, Mechanical Engineering or related field AND 9+ years technical engineering experience OR Bachelor's Degree AND 11+ years experience
• 10+ years designing and operating large-scale L2/L3 Ethernet fabrics for HPC/AI or hyperscale services
• 5+ years experience with Ethernet, RDMA/RoCEv2, congestion control, routing, and load balancing
• 5+ years experience with switch/NIC architecture and optics

Nice to Have:

• Experience optimizing networks for AI collectives and distributed training systems
• Familiarity with programmable data planes and NIC offloads
• Depth in buffer management and queue disciplines
• Experience with optic/PHY roadmaps and DC power/cooling constraints
• Contributions to standards bodies/consortia
• Proficiency in Python/Go and automation frameworks

Benefits & Perks

• Industry leading healthcare