Senior Solutions Architect, NVIDIA Cloud Partner Operations at NVIDIA

Department: Architect, Solutions

Language

Compensation

$224,000 – $356,500/yr

Setup: Remote
Location: California · Us, Île-de-France
Type: Full-time
Level: senior
Posted: Aug 13, 2026

Description

NVIDIA is hiring a Solutions Architect to improve Day 2 operations across its NVIDIA Cloud Partner ecosystem. The role works with partner engineers to troubleshoot and optimize large-scale GPU and AI infrastructure, prepare new platforms for production, improve reliability and economics, and convert validated solutions into reusable operating procedures, architectures, automation, and workflows. Candidates need a relevant advanced degree or equivalent experience, 12+ years in production infrastructure or cloud engineering, and deep hands-on expertise in GPU, HPC, or cloud operations technologies. The base salary is 224,000 USD to 356,500 USD, with equity and benefits, and applications were accepted until August 17, 2026.

Required Skills

Distributed infrastructure
Kubernetes
Python
Terraform
OpenTelemetry
Linux
GPU scheduling
Observability

Additional Information

Minimum Education: Bachelor's, master's, or PhD in Computer Science, Electrical or Computer Engineering, Physics, Mathematics, or a related field, or equivalent experience
Required Previous Experiences: 12+ years in production infrastructure, cloud engineering, solutions architecture, site reliability engineering, HPC, or a similar technical role; alternatively, 5+ years of exceptional specialist-level work in large-scale GPU or AI infrastructure
Experience building, operating, or improving distributed infrastructure under real production load
Deep expertise in at least one part of the Day 2 stack with hands-on work on large-scale GPU, HPC, or cloud infrastructure
Experience across the broader operating platform, including Kubernetes or Slurm, GPU scheduling, multi-tenancy, Prometheus, Grafana, OpenTelemetry, and automation tools
Strong Linux knowledge and Python, Bash, or similar experience for automation
Evidence-led troubleshooting across system boundaries and clear technical communication
Leading partner and cross-functional work without direct authority
Preferred Qualifications: Real-world experience operating a GPU cloud, HPC environment, or large-scale AI platform under customer load
Experience building or maturing a 24/7 operations function
Hands-on experience with NVIDIA rack-scale platforms or NVIDIA operations technologies
Experience improving fleet health or unit economics through benchmarking, infrastructure as code, GitOps, automated diagnosis, or agent-based remediation