General InformationReq # WD00099196
Career area: Artificial Intelligence
Country/Region: United States of America
State: North Carolina
City: Morrisville
Date: Wednesday, June 3, 2026
Working time: Full-time
Additional Locations:
* United States of America - North Carolina - Morrisville
Description and RequirementsJob 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 requirements 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:
- 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.
Additional Locations:
* United States of America - North Carolina - Morrisville
