Senior Production Engineer — DGX Cloud, Equity Options

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

Job summary

NVIDIA Corporation in Santa Clara, CA is seeking a Senior Production Engineer to build software and automation that make DGX Cloud services reliable, scalable, and safe to operate.

You will work on large-scale distributed systems spanning model endpoints, control plane services, and GPU/CPU compute infrastructure across AWS, Azure, Google Cloud and on-prem deployments. This role includes on-call duties, defining SLIs/SLOs, and deploying with GitOps to ensure robust production systems.

Qualifications

• 8+ years building or operating production services and large-scale distributed systems.
• Strong programming skills in Python or Go for production tools.
• Experience with IaC, configuration management, or GitOps.
• Strong knowledge of Linux, Kubernetes, containers, cloud infra, and networking.
• Understanding of SRE principles, including SLIs, SLOs, error budgets, incident response.
• Experience instrumenting services with metrics, logs, and traces.
• Clear technical communication across teams.
• BS/MS in Computer Science or equivalent.

Responsibilities

• Build and operate production software, automation, and tooling for control plane services.
• Improve reliability of inference and agentic platforms.
• Use IaC and GitOps to deploy, configure, validate, upgrade, and recover services.
• Define and instrument SLIs/SLOs and monitor health.
• Participate in on-call and incident response.
• Collaborate with model, platform, storage, networking, security, and GPU infra teams.

Skills

Python/Go

IaC/GitOps

Linux

Kubernetes

Networking basics

Education

BS/MS in Computer Science or equivalent

Tools

Terraform

Argo CD

CI/CD

Git

Job description

NVIDIA Corporation in Santa Clara, CA is seeking a Senior Production Engineer to build software and automation that make DGX Cloud services reliable, scalable, and safe to operate.

You will work on large-scale distributed systems spanning model endpoints, control plane services, and GPU/CPU compute infrastructure across AWS, Azure, Google Cloud and on-prem deployments. This role includes on-call duties, defining SLIs/SLOs, and deploying with GitOps to ensure robust production systems.