Senior Software Engineer, Cloud Infrastructure

NVIDIA•Santa Clara, CA

1d•$184,000 - $356,500•Remote

About The Position

NVIDIA is advancing accelerated computing and artificial intelligence through technology that powers breakthroughs in graphics, robotics, and autonomous vehicles. Our private cloud team builds and operates infrastructure that supports software engineers across graphics, deep learning, autonomous vehicles, and Omniverse. The platform spans thousands of servers, processes millions of automated jobs each day, and manages petabytes of storage. Join us to solve distributed systems challenges, develop agentic infrastructure workflows, and improve the reliability and efficiency of services that accelerate engineering across NVIDIA.

Requirements

Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
8+ years of infrastructure development experience, including delivering scalable cloud solutions from concept to production.
Strong object-oriented programming skills in Java or Go.
Background in artificial intelligence, machine learning, and data analytics, with the ability to apply these techniques to infrastructure.
Ability to diagnose complex distributed systems issues and drive root-cause resolution.
Effective collaboration across engineering teams and time zones, with ownership of customer needs and production outcomes.

Nice To Haves

A track record of operating large-scale distributed platforms and improving reliability, scalability, and operational efficiency.
Hands-on work with Kubernetes, container orchestration, and multi-cluster or multi-region environments.
Success building observability, alerting, and automated remediation systems that reduce operational toil.
Expertise in capacity planning, performance tuning, and preparing rapidly growing platforms for production.
Demonstrated ownership of ambiguous infrastructure challenges, from solution design through ongoing operation and continuous improvement.

Responsibilities

Design, build, and operate scalable cloud services for job execution, resource management, and storage.
Solve infrastructure challenges across Kubernetes, job scheduling, multi-region services, and automated recovery.
Develop agentic workflows that streamline infrastructure operations and reduce repetitive manual work.
Build observability, monitoring, and remediation capabilities to improve platform reliability and diagnose production issues.
Partner with engineering teams to understand customer needs and deliver solutions from concept through production.
Drive capacity planning, performance optimization, and production readiness as the platform grows.