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HPC Solutions Architect

Job in Town of Texas, Marathon County, Wisconsin, USA
Listing for: GTN Technical Staffing
Full Time position
Listed on 2026-10-16
Job specializations:
  • IT/Tech
    Systems Engineer, Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 150000 - 190000 USD Yearly USD 150000.00 190000.00 YEAR
Job Description & How to Apply Below
Location: Town of Texas

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
  • Infini Band, 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.
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