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Designs and operates multi-tenant SDN, VPC overlays, and high-performance InfiniBand or RoCE GPU network fabrics. Responsibilities include tenant isolation, cross-region routing, congestion control, network automation, change management, fault localization, architecture standards, security boundaries, and observability for a large-scale multi-region GPU cloud.

Design, tune, and maintain GPU hardware and fabric integrations for containerized AI workloads. Optimize host networking (RDMA, SR-IOV, RoCEv2, InfiniBand), implement GPU slicing (MIG, vGPU), build DCGM-based remediation pipelines, profile kernel/driver/runtime (CUDA, NCCL), and collaborate with scheduling/storage teams. Lead investigations, enforce bare-metal provisioning and firmware/OS standards, mentor engineers, and document the AI hardware stack.

Architect and scale high-cardinality observability and telemetry infrastructure for AI cloud platforms. Build Kubernetes exporters, eBPF diagnostics, hardware and network monitoring, dashboards, alerting, and GPU/network utilization billing pipelines. Establish telemetry standards for AI workloads, support proactive remediation, collaborate with GPU and scheduling teams, lead architecture reviews, and mentor engineers. The role requires expertise in Go, Kubernetes, Prometheus/OpenTelemetry, Linux performance tuning, eBPF, AI hardware metrics, and large-scale cloud or HPC telemetry systems.

Build and maintain cycle-approximate and analytical full-chip performance models (tile array, NoC, memory, IO) in C++/SystemC and Python; analyze LLM/CNN workloads and rooflines; model traffic, contention, memory QoS; run architectural sweeps and provide recommendations; collaborate with compiler and design teams; validate models against RTL/emulation/silicon and deliver reporting/dashboards for leadership.

Design and produce visual assets and motion graphics for digital, print, and video campaigns. Ensure brand consistency, collaborate with marketing/product teams, manage multiple projects, prepare final files for production, and maintain an organized asset library.

Design and build distributed systems for AI workloads, improve reliability and efficiency, and develop infrastructure automation tools.

Architect and build a highly available Kubernetes control plane for an AI-native cloud platform managing thousands of clusters. Develop Operators and CRDs, optimize etcd, implement multi-tenant security, enable zero-downtime upgrades and federation, and integrate with GPU orchestration systems. Lead distributed systems architecture, reliability engineering, design reviews, and team mentorship while preventing control-plane failures from affecting customer workloads.

Own end-to-end reliability for a customer-facing GPU cloud serving workloads across 100–10,000 GPUs. Responsibilities include operating Kubernetes GPU clusters, managing multi-tenant isolation, automating bare-metal provisioning, defining SLIs/SLOs/SLAs, handling incidents and customer communications, building observability with Prometheus and Grafana, implementing infrastructure as code and GitOps, and developing automated remediation and self-service operational tooling.

Lead a team in verifying complex IC designs, develop verification strategies, and ensure high-quality silicon through advanced methodologies and collaboration.

The Enterprise Systems Consultant will support daily operations of business systems, manage system-related requests, assist in implementation activities, and enhance business processes.