Principal Software Engineer, DGX Cloud Production Engineering

Nvidia

Confirmed live today Low trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Employment: Full-time
Posted: 162 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Similar $201k

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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 · Principal Software Engineer, DGX Cloud Production Engineering

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The Principal Software Engineer, DGX Cloud Production Engineering joins the team responsible for scaling GPU infrastructure across internal, partner, and cloud environments. This role involves defining the technical strategy for cluster operations, building automation, GitOps, and Day 2 reliability for large-scale GPU clusters. You will lead the design and implementation of systems for cluster lifecycle, validation, repair, upgrades, and observability while establishing patterns for Kubernetes-based operations. Key responsibilities include eliminating operational toil through software, APIs, and agent-assisted workflows while setting standards for SLOs and incident response. The role requires deep experience with Kubernetes, Linux, and infrastructure automation using Go or Python. You will solve complex infrastructure problems by building durable software and operating models for GPU clusters across NVIDIA Cloud Partners and on-prem environments.

What does a Software Engineer earn in California?

Median $214500 from 1193 postings across 76 companies.

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Skills

Kubernetes Go Python Linux GitOps GPU Clusters Infrastructure Automation Distributed Systems Cloud Infrastructure APIs Observability SLOs Incident Response BMaaS VMaaS Multi-cloud High-Performance Computing

What you'll do

Define and execute the technical strategy for DGX Cloud cluster operations and Day 2 reliability.
Build automation, GitOps, and systems for cluster lifecycle, validation, repair, and upgrades.
Establish operational patterns for Kubernetes-based GPU clusters across partner and on-prem environments.
Eliminate operational toil by developing software, APIs, and agent-assisted workflows.
Set technical standards for production readiness, SLOs, incident response, and handoff gates.
Design and implement observability systems for large-scale GPU infrastructure.
Mentor engineers and influence platform, infrastructure, storage, networking, and security teams.

What we're looking for

15+ years of experience building and operating large-scale distributed systems or cloud infrastructure.
Deep experience with Kubernetes, Linux, infrastructure automation, and production operations.
Strong programming experience in Go, Python, or similar.
Proven ability to lead complex cross-org technical initiatives.
Experience designing reliable systems with clear SLOs, observability, incident response, and automation.
BS/MS in Computer Science or equivalent experience.
Experience with GPU clusters, AI/ML infrastructure, Kubernetes operators, GitOps, BMaaS/VMaaS, managed Kubernetes, or multi-cloud fleet operations (preferred).
Experience building internal platforms, control planes, lifecycle automation, or production readiness frameworks (preferred).