HPC Orchestration Architect
Location: Dallas, TX
Work Arrangement: Hybrid
Employment Type: Direct Hire
Relocation: Available for qualified non-local candidates
Compensation: Competitive Base Salary + Performance Bonus
Benefits: 100% Company-Paid Family Benefits
Overview
Our client is seeking an experienced HPC Orchestration Architect to define and evolve the orchestration architecture supporting a large-scale high-performance computing and AI infrastructure platform.
This role will own architecture across compute orchestration, virtualization, containers, Kubernetes, and resource management, helping ensure highly scalable and highly available infrastructure can support demanding research, AI/ML, simulation, and scientific computing workloads.
The HPC Orchestration Architect will work closely with compute, storage, networking, and platform engineering teams to develop cohesive reference architectures, evaluate emerging technologies, and translate complex workload requirements into scalable production solutions.
This is a highly technical architecture role for someone who understands how compute, GPUs, storage, networking, virtualization, and Kubernetes must work together as an integrated HPC platform.
Key Responsibilities
- Own the architecture and long-term strategy for compute orchestration across large-scale HPC and accelerated computing environments.
- Design highly scalable, resilient, and distributed systems supporting demanding research, AI/ML, and scientific workloads.
- Define Kubernetes and container orchestration architectures supporting large-scale compute platforms.
- Evaluate existing and emerging HPC, virtualization, container, and orchestration technologies against business, performance, and operational requirements.
- Develop reference architectures and technical standards for implementation by infrastructure and engineering teams.
- Partner with compute, storage, and networking architects to ensure orchestration decisions align with the overall HPC platform architecture.
- Evaluate resource placement, scheduling, workload isolation, utilization, and performance tradeoffs across CPUs, GPUs, and other accelerators.
- Guide engineering teams through architecture implementation and ensure solutions meet scalability, reliability, and engineering quality standards.
- Identify opportunities to improve infrastructure automation, developer velocity, operational efficiency, and platform reliability.
- Establish data-driven methods for measuring and improving platform performance, capacity, utilization, and operational constraints.
- Evaluate new technologies through technical research, proof-of-concept testing, benchmarking, and production validation.
- Support architecture decisions involving Kubernetes clusters, virtualization platforms, containers, GPU infrastructure, and distributed systems.
- Work directly with technical stakeholders and customers to understand workload requirements and translate them into scalable infrastructure designs.
- Stay current on emerging HPC, AI infrastructure, cloud-native, Kubernetes, and accelerated computing technologies.
Required Qualifications
- Strong experience designing or architecting large-scale HPC, AI infrastructure, cloud, or distributed computing environments.
- Deep understanding of compute architecture, including CPUs, GPUs, accelerators, and their role within large-scale distributed systems.
- Strong hands-on experience with Kubernetes, including building, deploying, scaling, and operating production Kubernetes clusters.
- Deep knowledge of container technologies, container orchestration, virtualization, and workload management.
- Understanding of Kubernetes resource management, scheduling, placement, isolation, and performance optimization.
- Experience designing highly available and scalable distributed systems.
- Strong Linux expertise, including system-level optimization, performance profiling, troubleshooting, and kernel-level tuning.
- Experience with HPC clusters, parallel computing environments, or large-scale accelerated compute platforms.
- Understanding of how compute, networking, and storage architecture interact to influence workload performance.
- Familiarity with distributed and parallel storage platforms such as VAST Data, Lustre, or similar technologies.
- Experience evaluating infrastructure technologies through benchmarking, proof-of-concept environments, and performance analysis.
- Ability to translate technical and business requirements into scalable infrastructure architectures.
- Strong communication skills with the ability to work across architecture, engineering, operations, vendors, and technical customers.
Preferred Experience
Experience with one or more of the following is highly valued:
- Large-scale GPU or AI/ML clusters
- NVIDIA GPU infrastructure and accelerated computing
- Kubernetes scheduling and advanced resource management
- HPC workload orchestration and scheduling platforms
- Bare-metal and virtualized compute environments
- Infrastructure automation and platform engineering
- Distributed and parallel storage
- Scientific computing, simulation, or research workloads
- Multi-cluster or geographically distributed Kubernetes environments
- Cloud-native infrastructure and hybrid cloud architectures
Education
Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, Physics, or a related technical discipline preferred. Equivalent advanced professional experience in HPC, distributed systems, platform engineering, or large-scale infrastructure will also be considered.
Benefits
- Competitive base salary
- Performance bonus
- 100% company-paid family medical benefits
- Relocation assistance available for qualified non-local candidates
- Opportunity to architect infrastructure supporting large-scale HPC, AI, and accelerated computing environments