Cluster Network Engineering Lead

Skills

About the Role

You will lead the design and operation of AI cluster network fabrics, owning InfiniBand and RoCE architectures, RDMA performance, and fabric reliability for large-scale training and inference workloads. You will define fabric evolution, congestion control, topology, observability, vendor strategy, migration plans, and engineering standards while mentoring senior engineers and resolving architecture escalations.

Requirements

• Demonstrated experience in hyperscale networking, HPC fabrics, RDMA systems, or distributed systems networking at large scale
• Deep expertise in ECMP, adaptive routing, queueing theory, network telemetry pipelines, InfiniBand, and optical systems
• Proven experience designing and operating AI or HPC interconnects
• Strong knowledge of network behavior under distributed training frameworks and collective communication libraries such as NCCL and UCX
• Experience leading technology transitions across multiple hardware generations and mixed-vendor environments
• Ability to work credibly with hardware vendors, datacenter teams, software platform leaders, and executive stakeholders

Responsibilities

• Define long-range architecture for AI fabric evolution across RoCE, InfiniBand, Clos, spine-leaf, mesh, and optical fabric designs
• Lead migration from 100G to 400G, 800G, and 1.6T
• Own congestion control strategy, queue management, path diversity, and routing policy
• Drive topology decisions that improve NCCL all-reduce performance, completion times, latency stability, and fault containment
• Establish observability standards for fabric telemetry, queue behavior, packet loss, jitter, retries, and job impact
• Set cable plant strategy across fiber topology, optics qualification, and DAC/AOC standards
• Lead vendor engagement and define upgrade and migration playbooks
• Mentor principal and staff engineers and serve as the final escalation point for fabric architecture decisions