Senior Solutions Architect, NVIDIA Cloud Partner Operations

Nvidia

Confirmed live today High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $224,000–$356,500 / yr
Employment: Full-time
Posted: 75 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $204k

This role $290k

$145k $379k

below market most similar roles pay here above market

This role pays more than 91% of similar roles. Most pay $172,066–$235,750 — the blue band above. At the midpoint, this role pays about $290k versus about $204k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1623 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.

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At a glance

TL;DR · Senior Solutions Architect, NVIDIA Cloud Partner Operations

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The Senior Solutions Architect, NVIDIA Cloud Partner Operations joins the team to elevate Day 2 operations across the NVIDIA Cloud Partner ecosystem. This role involves solving complex production problems at scale, such as maintaining service health, improving performance, and optimizing economics for AI clouds. You will work alongside partner engineers to prototype solutions, validate them under representative loads, and create reference architectures, automation, and agentic workflows. Key technologies include DCGM, BMC/Redfish, InfiniBand, NCCL, UFM, Lustre, and VAST Data. You must also utilize Kubernetes, Slurm, Prometheus, Grafana, Terraform, Ansible, and Argo CD. The role requires deep expertise in GPU, HPC, or cloud infrastructure to address technical challenges involving GPU scheduling, multi-tenancy, and firmware lifecycles while improving reliability and unit economics for partners.

What does a Solutions Architect earn in California?

Median $235750 from 57 postings across 11 companies.

See salary data

Skills

HPC Kubernetes Slurm Terraform Ansible Argo CD Python Bash Prometheus Grafana OpenTelemetry InfiniBand Lustre IBM Storage Scale WEKA VAST Data NCCL DCGM BMC/Redfish GitOps Linux

What you'll do

Solve complex Day 2 operations problems by identifying root causes and prototyping validated solutions for cloud partners.
Develop operating models for new NVIDIA platforms, capacity, and services before they are deployed to customers.
Improve cloud reliability, performance, and economics using metrics like incident frequency and cost per token.
Identify and close gaps in partner telemetry, security, incident response, and automated tooling.
Convert validated technical solutions into reference architectures, operating procedures, and automated workflows for the ecosystem.
Analyze patterns across partners to provide field evidence to NVIDIA product and engineering teams for permanent fixes.
Train partner engineering teams to operate and maintain their own cloud infrastructure independently.

What we're looking for

BS, MS, or PhD in Computer Science, Electrical or Computer Engineering, Physics, Mathematics, or a related field, or equivalent experience.
12+ years in production infrastructure, cloud engineering, solutions architecture, site reliability engineering, HPC, or a similar technical role.
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, including GPU, HPC, or cloud infrastructure.
Working experience with Kubernetes or Slurm, GPU scheduling, Prometheus, Grafana, OpenTelemetry, and automation tools like Terraform or Ansible.
Strong Linux knowledge and proficiency in Python or Bash to automate measurement, diagnosis, validation, or remediation.
Real world experience operating a GPU cloud, HPC environment, or large-scale AI platform under customer load (preferred).

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