HPC Solutions Architect

GTN Technical Staffing; Town of Texas (WI); On-site; USD 150,000 - 190,000; Full time

Job summary

GTN Technical Staffing's client seeks an HPC Customer Solutions Architect to lead design, integration, and delivery of HPC and AI infrastructure solutions across GPU/CPU compute, storage, networking, Kubernetes, orchestration, and security.

You will translate client requirements into scalable, production-ready architectures, guide PoC, benchmark, and optimize workloads, and collaborate with engineering, product, and operations.

Qualifications

• Strong technical expertise across GPU/CPU architectures and NVIDIA CUDA ecosystem.
• Experience with Slurm and Kubernetes in HPC environments.
• Storage systems such as Lustre, GPFS/Spectrum Scale, Ceph, or similar.

Responsibilities

• Lead customer engagement and technical discovery to capture workload requirements and performance targets.
• Design end-to-end HPC and AI architectures across compute, storage, networking, orchestration, and security.
• Provide technical leadership during deployment, integration, and production handoff.
• Develop architecture blueprints, integration plans, and technical documentation.
• Lead customer workshops, architecture reviews, and technical presentations.

Skills

GPU and CPU architectures

NVIDIA CUDA ecosystem

Slurm

Kubernetes

InfiniBand RDMA RoCE

Storage platforms Lustre GPFS Ceph

Linux systems performance tuning

Architectures design & workload分析

Customer-facing communication

Education

Bachelor's/Master's in CS/Engineering/Physics

Tools

Ansible

Terraform

Job description

Compensation: Competitive Base Salary + Performance Bonus

Overview

Our client is seeking an HPC Customer Solutions Architect to lead the technical design, integration, and delivery of high-performance computing and AI infrastructure solutions.

This is a highly technical, customer-facing role focused on designing scalable architectures across GPU/CPU compute, storage, networking, Kubernetes, orchestration, and security. The position spans the full solution lifecycle from technical discovery and workload analysis through proof-of-concept, deployment, and ongoing optimization.

The ideal candidate brings deep HPC and AI infrastructure expertise, strong hands-on system design and performance tuning experience, and the ability to translate complex customer requirements into scalable, production-ready solutions.

Key Responsibilities

Customer Engagement & Technical Discovery

• Work directly with customers to understand workload requirements, performance targets, and technical objectives.
• Lead technical discovery sessions focused on application behavior, bottlenecks, scalability, and infrastructure requirements.
• Serve as a trusted technical advisor throughout the solution lifecycle.
• Design end-to-end HPC and AI architectures across compute, storage, networking, orchestration, and security.
• Recommend hardware and software solutions aligned with performance, scalability, reliability, and efficiency goals.
• Develop architecture blueprints, integration plans, and technical documentation.
• Design solutions supporting GPU-intensive AI/ML, LLM, and advanced compute workloads.

Performance & Workload Optimization

• Support proof-of-concept, benchmarking, and performance-validation initiatives.
• Perform workload profiling, system tuning, and infrastructure optimization.
• Identify bottlenecks across compute, storage, networking, and orchestration layers.
• Recommend improvements that increase workload performance, scalability, and resilience.

Implementation & Delivery

• Provide technical leadership during deployment and integration.
• Partner with customers and internal Engineering, Product, and Operations teams throughout implementation.
• Support solutions from architecture through production deployment and optimization.
• Troubleshoot complex infrastructure and workload issues during delivery.

Technical Leadership

• Maintain expertise across emerging HPC, AI, GPU, storage, networking, and orchestration technologies.
• Build relationships with technology partners across GPU, networking, and storage ecosystems.
• Contribute to reference architectures, reusable design patterns, and technical best practices.
• Lead customer workshops, architecture reviews, and technical presentations.

Required Qualifications

• Strong technical expertise across:
• GPU and CPU architectures
• NVIDIA / CUDA ecosystem
• Slurm and Kubernetes
• InfiniBand, RDMA, and RoCE
• Lustre, GPFS / Spectrum Scale, Ceph, VAST, or similar storage platforms
• Kubernetes and container orchestration
• Identity, encryption, and infrastructure security
• Strong Linux systems knowledge, including tuning and performance analysis.
• Experience translating workload requirements into detailed technical architectures.
• Experience with proof-of-concept, benchmarking, or workload optimization.
• Strong customer-facing communication and presentation skills.
• Ability to work effectively with engineering, product, operations, and executive stakeholders.

Preferred Experience

• AI/ML, LLM, GPU, or HPC workloads.
• NVIDIA GPU infrastructure.
• Automation and Infrastructure-as-Code.
• Workload migration and performance engineering.
• Next-generation GPU and high-speed interconnect technologies.
• Bachelor's or Master's degree in Computer Science, Engineering, Physics, or related field.
• Relevant cloud, Linux, networking, Kubernetes, or security certifications.