Lead AI Infra Architect—GPU-Scale Infrastructure

NVIDIA; Austin (TX); On-site; USD 184,000 - 287,500; Full time

Job summary

NVIDIA in Austin, TX is seeking a senior technical specialist to architect and scale high‑performance AI infrastructure, both on‑prem and cloud, while supporting sales teams and maintaining customer relationships.

You will work with Kubernetes, Slurm, Docker, and NVIDIA systems, traveling ~25–30% and collaborating across engineering and management to ensure successful deployments and customer satisfaction.

Qualifications

• BS or MS in Engineering, Electrical Engineering, Physics, or Computer Science (or equivalent)
• 5+ years in high-tech IT with NCP, CSP, site reliability, and virtualization (VMware, Linux KVM)
• 5+ years of Kubernetes, Slurm, Docker experience
• Proficiency with AI tools (Claud, Codex, Perplexity), Redfish, Grafana, and Prometheus
• Strong multitasking and prioritization abilities
• Excellent written and oral English communication you can collaborate with management and engineering teams

Responsibilities

• Architect and scale high-performance AI infrastructure on‑prem or cloud
• Be a technical specialist supporting sales account managers
• Cultivate technical relationships with engineers, management, and architects at key accounts
• Provide on‑site hardware/software problem solving focusing on deep learning inference
• Lead product lifecycle from design‑in to end‑of‑life with strong execution
• Maintain NVIDIA infrastructure components at customer sites and collect findings
• Deliver training to direct sales teams and channel partners
• Travel about 25–30%

Skills

Communication

Time management

Prioritization

Education

BS/MS in Engineering/CS/Physics

Tools

Kubernetes

Slurm

Docker

VMware

Linux

Redfish

Grafana

Prometheus

Job description

NVIDIA in Austin, TX is seeking a senior technical specialist to architect and scale high‑performance AI infrastructure, both on‑prem and cloud, while supporting sales teams and maintaining customer relationships.

You will work with Kubernetes, Slurm, Docker, and NVIDIA systems, traveling ~25–30% and collaborating across engineering and management to ensure successful deployments and customer satisfaction.