HPC Orchestration Architect | Kubernetes at AI Supercomputer Scale

Saragossa; Dallas (TX); On-site; USD 180,000 - 250,000; Full time

Job summary

Saragossa in Dallas is seeking a senior solutions architect to own the design of compute, virtualization, and Kubernetes orchestration across our platform.

You will evaluate HPC technologies, drive developer velocity, and work directly with clients to design scalable AI/ML and scientific computing solutions.

Candidates should have 10+ years of experience, Kubernetes clusters for GPU/HPC workloads, and deep CPU/GPU architecture knowledge.

Qualifications

• 10+ years of senior architecture experience.
• Built, deployed, and scaled Kubernetes clusters for GPU/HPC workloads.
• Strong knowledge of CPU/GPU architectures and resource placement.
• Experience tuning Linux kernels or profiling performance.
• Familiarity with HPC parallel file systems (VAST) is a plus.

Responsibilities

• Own the design of compute, virtualization, and Kubernetes orchestration across the platform.
• Evaluate emerging HPC technologies and provide direction to engineering teams.
• Drive improvements in developer velocity.
• Work with clients to capture requirements and design scalable AI/ML and scientific computing solutions.

Skills

Kubernetes architecture

Cloud platform design

Linux performance tuning

CPU/GPU architecture

Client interaction

Tools

GPU clusters

HPC workloads

VAST file system

Job description

Join a fast-growing company building a modern, AI-focused cloud platform from the ground up. They're in the middle of a $4B data center build with two more already planned, and their infrastructure supports large-scale scientific research, simulation, and AI/ML workloads.

This is a senior architecture role, owning the design of compute, virtualization, and Kubernetes-based orchestration across the platform. You'll evaluate emerging HPC technologies, give engineering teams clear direction, and drive improvements in developer velocity. The role also includes working directly with clients to capture requirements and design scalable solutions for AI/ML and scientific computing.

The ideal candidate has 10+ years of experience and has built, deployed, and scaled Kubernetes clusters, ideally for GPU or HPC workloads. A strong understanding of CPU, GPU, and accelerator architectures and how resource placement affects performance is key, along with Linux kernel tuning or performance profiling. Familiarity with parallel file systems like VAST is a plus.

The role is based in Dallas. Sponsorship is not available. Compensation can reach $180,000-250,000 base with additional bonus offered.