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Lambda is a leader in AI cloud infrastructure serving tens of thousands of customers, from AI researchers to enterprises and hyperscalers. The company's mission is to make compute as ubiquitous as electricity and give everyone access to superintelligence.
You will architect high-performance networking solutions that power cloud platforms, with a focus on ultra-low-latency and high-bandwidth connectivity for large-scale GPU clusters and multi-tenant environments. Your responsibilities include:
- Define network topology and architectural patterns for large-scale GPU clusters, storage backends, and multi-tenant environments
- Evaluate, benchmark, and select next-generation network technologies (InfiniBand NDR/XDR, RoCE, 400G-1.6T Ethernet, Ultra Ethernet, ESUN, OCI, etc.) to meet AI workload requirements
- Develop and maintain network architecture standards, reference designs, and scalability roadmaps for multi-site and hybrid environments
- Partner with compute and storage architects to ensure seamless end-to-end data flow and fault tolerance
- Guide network automation strategies and tooling to enable efficient provisioning, telemetry, and operational visibility
- Mentor engineers and cross-functional teams on advanced network concepts, troubleshooting, and architectural best practices
This is a staff-level individual contributor role with significant mentorship and cross-functional influence responsibilities. You will work 4 days per week in the San Jose office (First St), with Tuesday designated as the work-from-home day.
REQUIREMENTS:
- 7+ years of proven experience architecting high-performance data center networks, preferably for HPC, AI/ML, or large-scale cloud infrastructure
- Deep expertise with InfiniBand (HDR/NDR) and advanced Ethernet fabrics, including RoCE and RDMA protocols
- Strong understanding of data center switching architectures, congestion control (PFC, ECN), QoS, and network virtualization technologies (VXLAN, EVPN)
- Skilled in designing for low-latency and high-throughput data paths, including GPU-to-GPU and storage traffic optimization
- Expertise with BGP-based fabric design, including eBGP underlays, MP-BGP EVPN, ECMP, route policy, and convergence
- Experience with SDN, APIs, automation, and network telemetry
- Strong optical networking competency, including transceiver technologies, fiber types and topologies, link budgets, breakout architectures, and WDM
- Experience building resilient, fault-tolerant high-performance network architectures with redundancy, failover, and high availability
- Excellent communication and leadership skills, capable of influencing technical decisions across diverse teams
- Strong ownership and can-do attitude; self-starter comfortable working in ambiguity
NICE TO HAVE:
- Hands-on experience with AI workload profiling, collective communication patterns (NCCL, MPI), and network tuning for distributed training
- Familiarity with network automation frameworks and telemetry tools
- Exposure to DPU/SmartNIC technologies, including NVIDIA BlueField
- Knowledge of large-scale, multi-site interconnect design, including DWDM or metro/long-haul networking
- Experience collaborating with hyperscale or enterprise customers on highly customized network designs
