Network Solutions Architect, AI Factory Services

Job Summary Lenovo seeks a highly experienced Network Solutions Architect to join the Hybrid Cloud Solutions and AI Offering Engineering team within SSG. This senior-level role designs, deploys, validates, and optimizes high-performance network infrastructure for Lenovo's AI Factory and GigaFactory service offerings, supporting both enterprise-scale and hyperscale GPU environments powered by NVIDIA Spectrum-X Ethernet and InfiniBand fabrics. The architect will develop network reference architectures, deployment runbooks, performance validation procedures, and field-ready engineering documentation consumed by Lenovo Professional Services and Managed Services teams globally. This includes GPU cluster fabric design, BlueField DPU architectures, multi-tenant network isolation, high-performance RDMA and RoCEv2 deployments, and production-scale AI infrastructure supporting large distributed training and inference workloads. The ideal candidate brings deep expertise in NVIDIA Spectrum-X, Quantum InfiniBand, and BlueField DPU technologies, along with hands-on experience architecting, deploying, validating, and troubleshooting large-scale GPU clusters. Experience supporting hyperscale AI infrastructure, high-density liquid-cooled environments, GPU cluster bring-up, infrastructure validation, performance tuning, and customer-facing technical engagements is highly desired. Key Responsibilities AI Fabric Architecture & Design Design GPU cluster network architectures for NVIDIA AI Factory environments utilizing: Spectrum-X Ethernet (Spectrum-4 SN5600 + BlueField-3 DPUs) for enterprise deployments Quantum XDR InfiniBand and Spectrum Ethernet for rack-scale GigaFactory deployments Design and validate large-scale AI fabrics supporting RDMA, RoCEv2, GPUDirect, NCCL collectives, and high-bandwidth GPU-to-GPU communications. Develop rail-optimized InfiniBand topologies and Spectrum-X Adaptive Routing, SHARP, congestion management, and performance optimization strategies for AI training and inference environments. Contribute to architecture decisions supporting large-scale distributed AI and HPC workloads. Deployment, Validation & Performance Engineering Lead network bring-up, validation, and production-readiness activities for GPU infrastructure. Develop and validate RDMA/RoCEv2 configuration guides and deployment runbooks for AI and HPC environments. Establish performance baselines for: RDMA throughput RoCEv2 latency GPU communication efficiency Storage and network throughput End-to-end infrastructure readiness Design failure-domain isolation strategies and resilient network architectures for large-scale AI deployments. Support network architecture for high-density liquid-cooled GPU environments with power-aware design considerations. Troubleshooting & Operational Engineering Diagnose and resolve complex InfiniBand, Ethernet, RDMA, and GPU workload performance issues. Analyze congestion, telemetry, traffic patterns, link utilization, routing behavior, and fabric health to identify bottlenecks and optimize performance. Support root cause analysis and remediation of network, storage, and infrastructure issues impacting AI workload performance. Develop operational runbooks and troubleshooting procedures consumed directly by Lenovo field teams and customers. Multi-Tenant & Cloud Architecture Design multi-tenant networking architectures supporting AI Factory, NeoCloud, and managed-service provider environments. Implement namespace isolation, east-west traffic segmentation, secure tenant separation, and site resiliency aligned with NVIDIA Cloud Partner Reference Architectures. Design BlueField-3 DPU solutions utilizing DOCA for infrastructure offload, security services, observability, and service mesh capabilities. Customer & Cross-Functional Engagement Collaborate with Lenovo engineering, product, ISG, and services organizations to validate designs against NVIDIA reference architectures and future hardware roadmaps. Work directly with customers, partners, and delivery teams to translate AI workload

into production-ready infrastructure solutions. Provide technical leadership during customer engagements, infrastructure deployments, escalations, and architecture reviews. Support global deployments through approximately 40-50% travel, including customer workshops, implementation support, solution validation, and executive-level technical discussions. Basic Qualifications Bachelor's or Master's degree in Computer Science, Electrical Engineering, Information Technology, or related discipline. 5+ years of experience designing and deploying high-performance networking solutions for: AI infrastructure HPC environments GPU clusters Hyperscale cloud environments Experience designing and validating large-scale network fabrics supporting AI and distributed compute workloads. Experience with customer-facing technical consulting, architecture reviews, or deployment leadership. Preferred Qualifications NVIDIA AI Infrastructure Expertise Expert-level knowledge of: NVIDIA Spectrum-X Spectrum-4 SN5600 Ethernet Quantum InfiniBand (HDR/NDR/XDR) BlueField DPUs DOCA SDK RDMA and RoCEv2 AI Fabric & GPU Cluster Experience Experience supporting large-scale GPU cluster deployments and production AI environments. Deep understanding of: GPUDirect NCCL AI workload communication patterns GPU cluster validation and performance tuning Expertise in: Adaptive Routing SHARP Congestion control Rail-optimized InfiniBand architectures Networking & Infrastructure Strong experience with: BGP EVPN VXLAN MPLS OSPF IS-IS Leaf-Spine architectures Experience designing lossless Ethernet environments utilizing: PFC ECN DCQCN QoS Knowledge of high-performance storage networking and end-to-end infrastructure optimization. Automation & Observability Experience with: Python Ansible Terraform REST APIs Experience implementing infrastructure observability, telemetry, monitoring, and troubleshooting solutions for large-scale networks. Familiarity with data center operations, performance analytics, and capacity planning. Certifications Preferred certifications include: NVIDIA Certified Networking Professional NVIDIA InfiniBand Specialist Cisco CCNP Data Center Cisco CCIE Data Center OCI Networking Specialist AWS Solutions Architect Associate Hybrid Schedule on campus in Morrisville, NC. 3 days in office, 2 days work from home.