Senior Software Engineer, DGX Cloud Production Engineering

Segment (Twilio); Santa Clara (CA); On-site; USD 184,000 - 287,500; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA seeks a Senior Software Engineer to build and operate a large-scale GPU infrastructure for AI workloads. You'll automate large-scale GPU clusters, develop tools, and improve workflows within a production engineering team focused on Kubernetes.

With 8+ years of experience required, candidates should have strong skills in Python or Go, expertise in Linux and Kubernetes, and a BS/MS in Computer Science. Salary ranges from 184,000 to 356,500 USD based on level and experience, along with equity and benefits.

Qualifications

• 8+ years of experience building or operating production infrastructure.
• Experience with managing distributed systems in production.
• Clear communication and collaboration skills.

Responsibilities

• Build and operate automation for large-scale GPU clusters.
• Develop tools for cluster lifecycle operations.
• Partner with teams to ensure infrastructure readiness.

Skills

Python

Go

Kubernetes

Linux

Cloud infrastructure

Infrastructure automation

Education

BS/MS in Computer Science or equivalent experience

Tools

GitOps

Terraform

ArgoCD

Job description

NVIDIA DGX Cloud is building and operating large-scale GPU infrastructure for AI research and production workloads. We are looking for Senior Software Engineers to help build the automation, tooling, and operational systems that make GPU clusters reliable, scalable, and safe to run. This role is part of a production engineering team focused on Kubernetes-based infrastructure, GPU cluster operations, reliability, automation, GitOps, and Day 2 operability across DGX Cloud environments.

What you’ll be doing:

• Build and operate automation for large-scale GPU clusters across NVIDIA Cloud Partners (NCP) and on-prem environments.
• Develop tools and services for provisioning, validation, upgrades, monitoring, repair, and cluster lifecycle operations.
• Improve Day 0 / Day 1 / Day 2 workflows for cluster bringup, handoff, and production operations.
• Reduce manual production touches through APIs, GitOps, automation, and agent‑assisted workflows.
• Participate in on‑call, incident response, debugging, and durable follow‑up work.
• Partner with platform, storage, networking, security, and workload teams to make infrastructure production‑ready.

What we need to see:

• 8+ years of experience building or operating production infrastructure.
• Strong programming skills in Python, Go, or similar.
• Experience with Linux, Kubernetes, containers, cloud infrastructure, or infrastructure automation.
• Ability to troubleshoot distributed systems in production.
• Clear communication and ability to work across teams.
• BS/MS in Computer Science or equivalent experience.

Ways to stand out from the crowd:

• Experience with GPU infrastructure, Kubernetes operators, GitOps, Terraform, ArgoCD, or fleet automation.
• Experience with SLOs, on‑call, incident response, observability, and reliability practices.
• Exposure to BMaaS, VMaaS, managed Kubernetes, or multi‑cloud infrastructure.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.