Senior Cloud Infrastructure and Network Operations Solutions Architect

What You’ll Be Doing

What We Need to See

• BS/MS/PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or related fields, or equivalent experience.
• 5+ years of professional experience in data centre networking, fabric engineering or large-scale network operations roles.
• Fabric & Data Centre Networking: Deep understanding of data centre network architectures and RDMA fabrics—InfiniBand and RoCE/Ethernet—including topology and routing design (fat-tree, rail-optimised), congestion control, lossless/QoS configuration, and troubleshooting across NICs, switches and high-speed interconnects.
• NVIDIA Fabric Technologies: Hands-on experience with InfiniBand and UFM, Spectrum-X Ethernet, Cumulus Linux and/or SONiC, ConnectX and BlueField NICs/DPUs, and NVLink/NVSwitch systems—ideally including NMX-C / NMX-M partition operations on NVL72-class platforms.
• Linux & Switch Platforms: Deep knowledge of Linux (RedHat, Ubuntu) and switch operating systems, network OS internals, host networking and OS-level security, together with an understanding of the storage and compute traffic patterns of HPC/AI clusters.
• Automation, GitOps & Observability: Proficiency in Python and Bash scripting, configuration management and Infrastructure-as-Code tools (e.g. Ansible, Terraform), GitOps-based network configuration and firmware/upgrade management for large fleets, and observability stacks (Grafana, Loki, Prometheus) applied to fabric telemetry.
• Fleet Reliability & Customer Engagement: Demonstrated ability to measure and improve MTBI and job goodput on large GPU clusters—fault detection, drain and remediation workflows, SLO/error-budget definition and post-incident review—combined with a strong consultative background leading architectural reviews and presenting to executive stakeholders.

Ways to Stand Out from the Crowd

• Experience operating Kubernetes networking in GPU clusters—CNI plugins, multi-network attachment, SR-IOV and RDMA device plugins—and with the NVIDIA Network and GPU Operators for automated resource lifecycle management.
• Expertise with DOCA and DPU infrastructure services (e.g. DOCA DPF) for offloaded networking, security and storage services.
• Familiarity with fabric and GPU health telemetry—DCGM and XID diagnostics, link-level and switch counters, node-level health agents, and fleet-wide reliability intelligence.
• Knowledge of large-scale training traffic behaviour: collective communication (NCCL) tuning, rail alignment, and diagnosing network-bound performance regressions in distributed training jobs.
• Experience delivering multi-tenant network isolation for GPU-as-a-service estates—VRF/VLAN/EVPN segmentation, tenant partitioning and secure fabric handover between tenants.