Senior Cloud Engineer: Distributed Systems & AI Infra

NVIDIA Corporation; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits package

Job summary

NVIDIA Corporation is seeking a senior infrastructure-focused engineer to design, build, and operate scalable cloud services for job execution, resource management, and storage in a private cloud environment. You will tackle distributed systems, multi-region services, and automated recovery to keep the platform reliable and efficient.

The role emphasizes AI/ML awareness, capacity planning, and production readiness, with collaboration across time zones.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or related field, or equivalent experience.
• 8+ years of infrastructure development experience delivering scalable cloud solutions.
• Strong object-oriented programming skills in Java or Go.
• Background in AI, ML, and data analytics with application to infrastructure.
• Ability to diagnose complex distributed systems issues and drive root-cause resolution.

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.
• 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.

Skills

Java

Go

Kubernetes

Distributed systems

Observability

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Terraform

Job description

NVIDIA Corporation is seeking a senior infrastructure-focused engineer to design, build, and operate scalable cloud services for job execution, resource management, and storage in a private cloud environment. You will tackle distributed systems, multi-region services, and automated recovery to keep the platform reliable and efficient.

The role emphasizes AI/ML awareness, capacity planning, and production readiness, with collaboration across time zones.