HPC AI Solution Architect (S2S)

Role Overview

Work You'll Do

• Lead architecture for pursuits and active opportunities, including discovery, requirements, constraints, and target-state design.
• Define reference architectures for on-premises, cloud, and hybrid GPU platforms across compute, network, storage, security, software, and operations.
• Drive architecture trade-offs involving performance, scalability, reliability, locality, cost, time to value, and risk.
• Own technical solution strategy in proposals and RFPs, including assumptions, dependencies, sizing, and delivery approach.
• Facilitate client workshops and technical reviews and translate engineering detail into executive-ready communications.
• Engage C-suite client leadership during sales and delivery and support new business opportunities.
• Support go-to-market activities including industry events, conferences, and client briefings.

Required Qualifications

• At least 8 years of infrastructure architecture or engineering experience for large-scale platforms.
• At least 4 years designing or delivering GPU-accelerated AI, ML, or HPC platforms.
• At least 3 years of production Linux system administration.
• At least 3 years designing or operating distributed AI or HPC clusters in hybrid cloud environments.
• At least 2 years with high-performance networking or storage for AI or HPC.
• At least 2 years building Kubernetes or Red Hat OpenShift platforms with GPU operators, CUDA runtime, and lifecycle automation.
• At least 2 years using infrastructure as code tools such as Terraform and Ansible.
• At least two end-to-end reference architecture deployments with security, segmentation, runbooks, and validation testing.
• Experience in pre-sales or sales engineering, including discovery, demonstrations, proposals, or RFPs.
• Ability to travel approximately 50%.

Preferred Qualifications

• At least 2 years implementing AI or HPC cluster scheduling with Slurm and Kubernetes.
• Experience with multi-node distributed training and generative AI infrastructure patterns.
• Experience with AI agents and frameworks.
• Experience with high-throughput storage for AI or HPC.
• Experience with NVIDIA co-sell motions involving OEMs, cloud providers, or independent software vendors.

Compensation

• The estimated annual compensation range is $141,200 to $278,300.
• Compensation decisions consider skills, experience, training, licensure, certifications, geography, and business needs.
• Eligible employees may participate in a discretionary annual incentive program based on individual and organizational performance.

The Team