Principal Software Engineer, DGX Cloud Production Engineering

Nvidia

Confirmed live today High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CA
Salary: $272,000–$431,250 / yr
Employment: Full-time
Posted: 77 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 $199k

This role $352k

$107k $466k

below market most similar roles pay here above market

This role pays more than 99% of similar roles. Most pay $169,550–$228,187 — the blue band above. At the midpoint, this role pays about $352k versus about $199k 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 · Principal Software Engineer, DGX Cloud Production Engineering

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JOB TITLE: Principal Software Engineer, DGX Cloud Production Engineering NVIDIA is seeking a Principal Software Engineer to join the team building the next generation of their Kubernetes platform. This role focuses on developing foundational capabilities for self-service GPU infrastructure, managed Kubernetes control planes, and automation for large-scale AI environments. You will lead the architecture and development of core platform capabilities, including cluster management, fleet lifecycle, and day-2 operations. Responsibilities include designing highly reliable distributed systems and APIs for provisioning, upgrading, and remediating clusters across cloud and on-premises environments. You will utilize Go, Python, Rust, or C++ to build platform software and infrastructure control planes. The role requires deep expertise in Kubernetes internals, controllers, operators, and distributed systems design to solve complex problems in scalability, resilience, and operability for accelerated computing platforms.

What does a Software Engineer earn in California?

Median $214500 from 1193 postings across 76 companies.

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Skills

Kubernetes Go Python Rust C++ Distributed Systems GitOps APIs Bare-metal GPU HPC Cluster Management

What you'll do

Lead the architecture and development of core Kubernetes platform capabilities, including cluster management and control plane services.
Design and build highly reliable distributed systems and APIs for provisioning, managing, and upgrading Kubernetes clusters at scale.
Define technical requirements and production-readiness practices for declarative workflows and automation across the Kubernetes stack.
Diagnose and resolve complex platform issues spanning infrastructure, runtime, networking, hardware, and operations.
Improve the scalability, resilience, and operability of systems supporting large-scale AI deployments.
Influence engineering standards, architectural decisions, and long-term platform strategy across the organization.
Mentor senior engineers to improve design quality, execution, and engineering rigor.

What we're looking for

BS or MS degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
15+ years of relevant software engineering experience, including building and operating large-scale production systems.
Deep expertise in Kubernetes internals, APIs, controllers or operators, and cluster lifecycle management.
Strong background in distributed systems design, reliability, scalability, and failure recovery.
Proven experience building platform software, infrastructure control planes, or foundations for managed services.
Strong programming skills in one or more systems or cloud-native languages such as Go, Python, Rust, or C++.
Demonstrated ability to provide technical leadership across team boundaries and drive ambiguous, cross-functional initiatives.
Experience building Kubernetes platforms, managed services, or supporting AI and GPU platforms (preferred).

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