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Domain Architect - AI Networking (Nvidia ecosystem)
Summary
Founded in 1990, WWT brings together strategy, deep technical expertise and world-class partnerships to help public and private sector organizations design, build and scale intelligent AI, digital, cybersecurity, cloud and infrastructure solutions. Through its Advanced Technology Center (ATC)-a collaborative ecosystem featuring state-of-the-art hardware and software-WWT enables clients and partners to conceptualize, test and validate innovative technology and then deploy solutions at scale using its global integration and distributions capabilities.
With more than 14,000 team members and over 60 locations globally, WWT's culture-grounded in core values and leadership philosophies-has been recognized by Fortuneยฎ and Great Place to Work for its commitment to innovation, trust and creating a great place to work for all. WWT provides products and services to large enterprise, global service provider and public sector clients in up to 130 countries across six continents. Softchoice, a World Wide Technology company, supports commercial and SMB markets in the U.S. and Canada.
Want to work with highly motivated individuals on high-performance teams? Join WWT today!
What is the Solutions Consulting & Engineering Team and why join?
Solutions Consulting & Engineering is an organization that is customer-focused and solutions-led. We deliver end-to-end and emerging solutions to drive customer satisfaction and increase profitability and growth. Our world-class management consulting, delivery excellence, and engineering brilliance enable our success. We embody the OneWWT mindset by bringing the right talent at the right time from anywhere within WWT to solve our customer's problems. Our goal is to bring together business acumen with full-stack technical know-how to develop innovative solutions for our clients' most complex challenges.
About the Role
AI Factory Overview
WWT's AI Factory practice designs, builds, and delivers purpose-built AI infrastructure environments that enable organizations to deploy, scale, and operationalize advanced AI workloads. By integrating compute, networking, storage, software, and operational expertise into a validated reference architecture, the AI Factory team helps customers accelerate AI adoption while reducing deployment risk and complexity.
As a Domain Architect - AI Networking , you will serve as the technical authority for the design, deployment, and lifecycle management of high-performance AI network fabrics within WWT's AI Factory practice. Working closely with compute, storage, and software specialists, you will define and deliver scalable, low-latency, and lossless networking architectures that enable AI factories to operate at enterprise and hyperscale levels.
You will bridge architecture and execution, providing deep expertise across InfiniBand, Ethernet, and next-generation AI networking technologies while ensuring customers receive integrated, automated, and production-ready environments. As a trusted advisor and hands-on technical leader, you will help shape AI Factory solutions, support strategic client engagements, and establish the networking standards that power successful AI infrastructure deployments.
Your time will be split roughly 60/40 between delivering complex AI infrastructure (60%) and providing pre-sales subject matter expertise (40%). You will lead the physical provisioning of InfiniBand and Spectrum-X Ethernet fabrics for NVIDIA DGX SuperPOD, NVIDIA DGX BasePOD, and Cisco AI POD environments, ensuring clients inherit platforms that are genuinely ready for day-2 operations, while helping the sales team scope and cost future deployments.
Key Responsibilities
Delivery and implementation
High-performance fabric design
+ Architect and deploy non-blocking fat-tree (Clos) topologies using NVIDIA Quantum-2 (NDR) and Quantum-3 (XDR) InfiniBand switches, and NVIDIA Spectrum-4 Ethernet switches.
+ Implement rail-optimized network designs so GPU-to-GPU traffic aligns with compute-node PCIe topology, minimizing latency for NCCL collective operations.
+ Configure adaptive routing, congestion control, and quality of service (QoS) to prevent head-of-line blocking and guarantee lossless data delivery.
In-network computing and offload strategy
+ InfiniBand: enable and tune SHARP (Scalable Hierarchical Aggregation and Reduction Protocol) on Quantum switches to offload collective operations (AllReduce, ReduceScatter) from the GPU to the switch silicon.
+ Ethernet: architect high-performance Ethernet AI fabrics using SmartNIC/DPU offload (NVIDIA BlueField-3) to accelerate collective operations and isolate management traffic from the data path.
+ Evaluate and roadmap emerging Ultra Ethernet Consortium (UEC) standards as the practice transitions in-network collectives from proprietary InfiniBand toward open Ethernet.
+ Tune RoCEv2, PFC, and ECN on Ethernet fabrics and SmartNICs to approximate InfiniBand-class lossless behavior.
Fabric management, automation, and telemetry
+ Deploy NVIDIA UFM (Unified Fabric Manager) to manage InfiniBand subnets and NetQ for Ethernet fabric telemetry; implement PTP for nanosecond-level clock synchronization across the cluster.
+ Use automation and AI-assisted tooling to generate switch configuration from the P2P cabling schedule, LLD, and PDG, then validate every topology in NVIDIA DSX Air before it ever touches hardware.
+ Monitor fabric health continuously to identify slow receivers and link degradation in real time, and maintain Python and Ansible-based infrastructure-as-code for ongoing configuration management.
Layer 1 precision and performance engineering
+ Own the physical cabling strategy, defining cable schedules (DAC, AOC, or OSFP transceivers) that meet signal-integrity requirements over the required distances.
+ Validate the link budget to ensure optical loss stays within acceptable limits for 400G and 800G links.
+ Conduct acceptance and validation testing using NCCL tests to verify fabric performance against expected baselines.
Pre-sales SME and consulting
Technical scoping and estimation
+ Calculate the bisectional bandwidth required for a client's workload (for example, training typically requires 1:1 non-blocking; inference may tolerate 3:1 oversubscription), and produce accurate level-of-effort (LOE) estimates for statements of work.
Bill of materials validation and architecture
+ Own the technical accuracy of the network bill of materials, validating that every switch, transceiver, and cable is on the NVIDIA or OEM hardware compatibility list (HCL).
+ Manage the complexity of breakout cables (for example, 800G to 2x400G) and connector types (OSFP, QSFP112) to prevent on-site installation failures.
Client workshops
+ Educat...
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