HPC Kubernetes Solutions Architect (GPU Platforms)

HPC Kubernetes Solutions Architect (GPU Platforms)

Location: Dallas, TX (Hybrid)

Type: Direct Hire

• Competitive base salary + performance bonus
• 100% company-paid benefits

Overview

We are seeking an HPC Kubernetes Solutions Architect to lead the design, integration, and adoption of GPU-accelerated Kubernetes platforms supporting HPC, AI/ML, simulation, and scientific workloads.

This is a highly technical, customer-facing architecture role with ownership across the full solution lifecycle—from discovery and requirements gathering through architecture design, proof-of-concept delivery, deployment, and long-term optimization. The role serves as a trusted advisor to customers while also influencing internal product and engineering direction through real-world feedback.

The ideal candidate brings deep expertise across Kubernetes, GPU orchestration, and HPC environments, along with the ability to design scalable, high-performance platforms and guide customers through complex infrastructure transformations.

Key Responsibilities

Customer Engagement & Architecture Leadership

• Serve as the primary architectural point of contact for customers adopting GPU-accelerated Kubernetes platforms
• Capture workload requirements, performance objectives, and scaling needs, translating them into reference architectures and solution designs
• Lead customer workshops, technical design sessions, and architecture reviews

Kubernetes & GPU Platform Engineering

• Architect and operate Kubernetes clusters optimized for GPU workloads using NVIDIA GPU Operator, Network Operator, DCGM, and device plugins
• Integrate Multi-Instance GPU (MIG), GPU sharing, and advanced scheduling (Volcano, Slurm integration, kube-scheduler plugins)
• Design and implement multi-tenant Kubernetes environments with strong isolation and performance guarantees

Automation & Operator Development

• Develop or extend custom Kubernetes operators and controllers using Go or Python
• Automate HPC infrastructure services and platform operations
• Support Infrastructure-as-Code and GitOps practices using Terraform, Helm, Kustomize, ArgoCD, and FluxCD

Performance Optimization & Benchmarking

• Lead proof-of-concept and benchmarking initiatives to validate performance and scalability
• Utilize profiling tools and workload characterization methodologies to optimize GPU utilization and cluster performance
• Conduct performance tuning across compute, storage, and networking layers

Integration & Infrastructure Design

• Define integration strategies across compute, storage, networking, and orchestration layers
• Support CNI integrations (NVIDIA CNI, Multus, Cilium), distributed storage (Lustre, GPFS, Ceph, VAST), and container runtimes
• Ensure seamless integration with HPC schedulers and enterprise systems

Observability & Monitoring

• Implement monitoring and telemetry solutions using Prometheus, Grafana, DCGM Exporter, and OpenTelemetry
• Provide visibility into GPU health, cluster utilization, and workload performance

Cross-Functional Collaboration

• Partner with HPC, ML, DevOps, and platform teams to ensure scalability and performance in hybrid and on-prem environments
• Collaborate with product and engineering teams to influence roadmap and platform improvements
• Build relationships with ecosystem vendors including NVIDIA, networking providers, and storage partners

Innovation & Thought Leadership

• Stay current on GPU roadmaps, interconnect technologies (InfiniBand, RoCE, NVLink), and Kubernetes advancements
• Provide forward-looking guidance to customers on scaling and future architecture evolution
• Represent the organization in technical workshops, design sessions, and industry events

Required Experience

• Extensive experience designing and operating Kubernetes platforms in HPC or GPU-intensive environments
• Deep expertise across:

• NVIDIA GPU ecosystem (GPU Operator, device plugins, MIG, NVML, DCGM)
• Kubernetes internals (CRDs, RBAC, scheduler extensions, custom operators/controllers)
• High-performance networking (InfiniBand, RDMA, RoCE)
• Distributed storage integration for HPC workloads

• Proven ability to design scalable, secure, and resilient Kubernetes-based architectures
• Proficiency in Go or Python for operator development and automation
• Experience with workload profiling, benchmarking, and performance tuning
• Strong customer-facing skills with the ability to translate requirements into actionable architectures
• Experience collaborating across engineering, product, and operations teams

Preferred Experience

• Experience delivering end-to-end HPC or AI/ML solutions from design through deployment and optimization
• Familiarity with containerized HPC environments (e.g., Singularity/Apptainer)
• Experience with GitOps practices and CI/CD pipelines for Kubernetes platforms
• Contributions to open-source projects in Kubernetes or NVIDIA ecosystems
• Experience advising customers on future-state architectures and emerging technologies
• Bachelor’s or Master’s degree in Computer Science, Engineering, Physics, or related field
• Relevant certifications such as CKA, CKAD, CKS, AWS Solutions Architect, or Azure Solutions Architect Expert