HPC Network Engineering Manager - AI Infrastructure

Description

We are seeking an **HPC Network Engineering Manager \- AI Infrastructure** to guide architecture and technical direction for AI research and Kubernetes\-based GPU infrastructure. You will steer standards for InfiniBand/RDMA, Ethernet, Kubernetes networking, SmartNIC/DPU, and observability across large programs while mentoring senior engineers. Join us to shape reliable, scalable network platforms for massive distributed AI workloads—apply now. **Responsibilities** * Define and own a multi\-year architectural vision and roadmap for InfiniBand/RDMA and high\-speed Ethernet fabrics supporting massive GPU clusters and distributed AI/LLM workloads across the client portfolio * Govern evaluation and standardization of cluster network topologies such as Fat\-tree, Clos, Rail\-optimized, and Dragonfly, and set decision frameworks aligned to scale, performance, and cost constraints * Establish and enforce engineering standards for host\-side networking, including NIC configuration, drivers, firmware, IRQ affinity, NUMA placement, PCIe topology, and GPU\-to\-NIC communication paths * Drive strategic performance engineering across RDMA/RoCE, NCCL/MSCCL, and collective communication for multi\-node GPU training, and oversee resolution of the hardest systemic performance issues * Define the reference architecture for Kubernetes networking on GPU clusters, including CNI plugins, network policies, multi\-NIC pods, RDMA/GPU device plugins, and workload orchestration integration, and lead adoption across programs * Own strategy and governance for SmartNIC/DPU technologies such as NVIDIA BlueField, including SR\-IOV, offload, isolation, and security use cases, and align rollout with the broader infrastructure roadmap * Define enterprise network observability strategy, governing metrics, dashboards, alerts, congestion detection, latency tracing, SLO frameworks, and capacity/performance analysis methods * Provide technical leadership and mentorship to lead and principal engineers across networking, Kubernetes, storage, GPU infrastructure, observability, and AI research teams to drive cross\-functional alignment * Represent the principal technical authority in executive stakeholder forums by shaping direction, negotiating program trade\-offs, and ensuring delivery of reliable, scalable network platforms across engagements * Contribute to the engineering community through thought leadership, internal practice building, and representation at industry events **Requirements** * 9\+ years of experience in network, infrastructure, HPC, SRE, or similar engineering roles, with 5\+ years focused on HPC, AI/ML, or GPU cluster networking, including demonstrated technical leadership at the program or portfolio level (3\+ years) * Proven track record defining architecture and governing delivery for InfiniBand/RDMA fabrics, high\-speed Ethernet, and Linux networking in large\-scale, performance\-sensitive distributed compute environments * Authoritative expertise in host\-side networking (NICs, drivers, firmware) plus PCIe topology, NUMA awareness, and GPU\-to\-NIC affinity, with demonstrated ability to set enterprise standards and uplift engineering practices * Deep understanding of distributed AI training communication patterns, including NCCL\-based workloads and collective operations such as all\-reduce and all\-gather, with ability to drive workload\-network co\-design at scale * Authoritative knowledge of Kubernetes and container networking for GPU or distributed workloads, including CNI concepts, network policies, multi\-NIC patterns, and RDMA/GPU device integration, with experience defining reference architectures * Expert\-level mastery of RDMA networking, including InfiniBand, RoCE/RoCEv2, GPUDirect\-related patterns, congestion behavior, and performance tuning at very large scale * Mastery of Linux networking and host\-side troubleshooting, including IRQ affinity, MTU, offloads, and performance diagnostics, with ability to define repeatable diagnostic methodologies for broader teams * Demonstrated ownership of network observability and performance management strategy, including telemetry, traffic monitoring, congestion detection, latency analysis, SLOs, capacity planning, and alerting/troubleshooting across L1\-L4, fabric, and RDMA layers * Outstanding leadership, mentoring, stakeholder management, and executive communication skills, with proven experience leading multiple engineering teams, influencing C\-level client architecture decisions, and driving alignment across research and platform stakeholders * English language proficiency at an Advanced level (C1\) **Nice to have** * Hands\-on architectural and strategic experience with Azure Networking, Ethernet, and GPGPU/GPU technologies * Authoritative command of Grafana and Prometheus, plus Network Administration experience defining observability standards across an engineering organization * Proven ability to set strategy, govern, and scale Infrastructure as Code practices across multiple teams and programs * Proficiency in Python and UNIX shell scripting for automation, tooling, and improving engineering productivity * Track record of thought leadership through conference talks, publications, patents, or open\-source contributions in the HPC/AI networking domain