Senior AI Infra Architect – GPU & Kubernetes

Hamilton Barnes ?; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

Hamilton Barnes is seeking a Senior Solutions Architect to join its post-sales team, focusing on design and deployment of GPU-accelerated AI/ML workloads on a Kubernetes-native Platform-as-a-Service. You will act as a trusted technical advisor across the customer lifecycle, shaping architectures for enterprise-scale AI infrastructure.

You will collaborate with product and engineering to translate workload requirements into scalable architectures, deliver workshops and PoCs, and mentor junior

Qualifications

• 8+ years in infrastructure, platform, or solutions engineering, including 3+ years focused on AI/ML infrastructure or MLOps
• Deep, hands-on Kubernetes expertise (cluster lifecycle, workloads, operators, RBAC) plus direct experience with NVIDIA GPU infrastructure (H100/H200 preferred)
• Working knowledge of distributed training concepts (NCCL, tensor and pipeline parallelism) and GPU networking (GPU Operator, MIG, SR-IOV, IB/RoCEv2)
• Experience with LLM inference serving and optimisation (vLLM, NIM, TGI)
• Confident, credible communicator able to run technical discussions with engineers through to executive stakeholders; strong troubleshooting mindset and customer advisory presence

Responsibilities

• Design end-to-end AI/ML platform architectures spanning inference, training, and data pipelines for enterprise customers
• Develop reference architectures for GPU cluster deployment, LLM serving, and multi-tenant ML infrastructure
• Advise on GPU fabric topology, including NVLink, InfiniBand, and RoCEv2, for distributed training environments
• Act as the primary technical advisor and escalation point for assigned customers, leading root cause analysis on complex production issues
• Deliver technical workshops, proof-of-concept engagements, and executive-level presentations on AI infrastructure strategy
• Design observability strategies across DCGM, OpenTelemetry, eBPF, and GPU metrics pipelines
• Partner with customer platform, MLOps, and data science stakeholders to translate workload requirements into scalable architecture
• Feed customer insights back into the product and engineering roadmap, and mentor junior members of the Solutions Architecture team

Skills

Kubernetes expertise

NVIDIA GPU infrastructure

LLM inference serving

Distributed training concepts

Executive stakeholder communication

Root cause analysis

Tools

GPU Operator

MIG / SR-IOV

NCCL

InfiniBand / RoCEv2

OpenTelemetry / eBPF

Job description

Hamilton Barnes is seeking a Senior Solutions Architect to join its post-sales team, focusing on design and deployment of GPU-accelerated AI/ML workloads on a Kubernetes-native Platform-as-a-Service. You will act as a trusted technical advisor across the customer lifecycle, shaping architectures for enterprise-scale AI infrastructure.

You will collaborate with product and engineering to translate workload requirements into scalable architectures, deliver workshops and PoCs, and mentor junior