HPC Solutions Architect

HPC Solutions Architect

Location: Dallas, TX (Hybrid)

Type: Direct Hire

• Competitive base salary performance bonus

• 100% company-paid benefits

• Relocation available

Overview

We are seeking an HPC Solutions Architect to lead the design, integration, and delivery of advanced compute platforms supporting HPC, AI/ML workloads, and next-generation CaaS / GPUaaS environments.

This is a highly technical, customer-facing role focused on building scalable, high-performance architectures across compute, storage, networking, Kubernetes, and security domains. You will operate across the full solution lifecycle—from early-stage discovery and workload analysis through architecture design, proof-of-concept, deployment, and ongoing optimization.

The ideal candidate brings deep expertise in HPC and GPU-accelerated environments, with the ability to translate complex customer requirements into production-ready, scalable platform solutions in rapidly evolving AI infrastructure ecosystems.

Key Responsibilities

Customer Engagement & Technical Strategy

• Partner directly with customers to understand HPC, AI/ML, and GPUaaS / CaaS platform requirements, performance goals, and scaling challenges
• Lead technical discovery sessions to evaluate workloads, bottlenecks, and architecture trade-offs
• Serve as a trusted advisor across the full solution lifecycle

Solution Architecture & Platform Design

• Design end-to-end architectures across compute (CPU/GPU), storage, networking, orchestration, and security
• Architect solutions supporting GPU-as-a-Service (GPUaaS) and Container-as-a-Service (CaaS) delivery models
• Develop reference architectures, design blueprints, and integration frameworks

Performance Optimization & Workload Engineering

• Lead proof-of-concept, benchmarking, and validation efforts for HPC and AI workloads
• Perform workload profiling, system tuning, and performance optimization across distributed environments
• Optimize for scalability, efficiency, and reliability in GPU-accelerated platforms

Implementation & Solution Delivery

• Provide hands-on guidance during deployment to ensure successful integration into customer environments
• Partner with engineering, product, and operations teams to deliver end-to-end solutions
• Support deployment through production readiness and ongoing optimization

Cross-Functional Collaboration

• Collaborate with internal engineering and product teams to influence platform capabilities and roadmap
• Build relationships across GPU, networking, and storage vendor ecosystems
• Contribute to the evolution of HPC and AI platform offerings

Innovation & Technical Leadership

• Stay current on emerging technologies across GPUs, accelerators, interconnects, and orchestration frameworks
• Represent the organization in technical workshops, architecture reviews, and customer engagements
• Contribute to reusable frameworks, best practices, and reference architectures

Required Experience

• Proven experience in HPC solution architecture, distributed systems design, or large-scale AI infrastructure environments
• Strong expertise across:
• GPU and CPU architectures (NVIDIA ecosystem, CUDA)
• HPC and container-based schedulers (Slurm, Kubernetes)
• High-performance networking (InfiniBand, RDMA, RoCE)
• Distributed storage systems (Lustre, GPFS, Ceph, VAST)
• Kubernetes and container orchestration for HPC / AI workloads
• Security integration (identity, encryption, compliance)
• Experience designing or supporting CaaS and/or GPUaaS platforms or similar multi-tenant compute environments
• Strong Linux systems expertise including performance tuning and system-level optimization
• Ability to translate complex customer requirements into scalable architecture and implementation plans
• Strong communication skills with experience leading workshops, technical reviews, and customer engagements
• Experience working cross-functionally with engineering, product, and operations teams
• Ability to present complex technical concepts to both technical and executive audiences

Preferred Experience

• Experience delivering HPC or AI/ML workloads from design through deployment and optimization
• Familiarity with containerized HPC environments (Kubernetes, Singularity, etc.)
• Experience with automation, infrastructure-as-code, and platform engineering practices
• Background in proof-of-concept delivery, benchmarking, and workload migration
• Exposure to next-generation GPU architectures and high-speed interconnects
• Bachelor’s or Master’s degree in Computer Science, Engineering, Physics, or related field
• Relevant certifications (AWS, Azure, GCP, Kubernetes, Linux, networking)

Additional Requirements

• This position requires applicants to be currently authorized to work in the U.S. without employer sponsorship.
• We are unable to sponsor or take over sponsorship of employment visas at this time.