below marketmost similar roles pay hereabove market
This role pays more than
97%
of similar roles. Most pay
$169,550–$214,500
— the blue band above.
At the midpoint, this role pays about
$320k
versus about
$192k
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.
The Principal Software Engineer - Compute Infrastructure will join a dynamic team to lead the architectural vision for a massive global enterprise compute platform. You will define platform architecture for thousands of nodes and tens of thousands of VMs and containers using OpenShift and KubeVirt. Key responsibilities include operationalizing internal frontier-class AI inference systems, developing automated remediation pipelines, and managing hardware watchdogs for pre-release rack-scale GPU systems. You will drive capacity planning, design self-service APIs, and lead complex migrations of legacy workloads into modern Kubernetes orchestration. Required skills include deep expertise in Kubernetes, KubeVirt, and virtualization, alongside proficiency in Go, Python, Terraform, and OpenTofu. You must possess extensive experience in site reliability, hardware-level failure mitigation, and unified GitOps postures using ArgoCD.
What does a Software Engineer earn in California?
Median $214500 from 1193 postings across 76 companies.
Lead the architectural vision for a global enterprise compute platform running thousands of nodes and containers.
Define service tiers, SLAs, and automated cluster lifecycles for OpenShift and KubeVirt environments.
Build the operational foundation for internal AI inference platforms scaling to frontier-class models.
Develop automated remediation pipelines, hardware watchdogs, and telemetry for pre-release rack-scale GPU systems.
Perform capacity planning and develop proactive strategies for hardware supply constraints and public cloud bursting.
Design self-service architectures, APIs, and Terraform/OpenTofu providers to drive cultural adoption of standard platforms.
Lead the migration of massive legacy workloads and VDI environments into modern Kubernetes orchestration.
What we're looking for
Bachelor’s degree in Engineering, Computer Science, Mathematics, or a related field, or equivalent experience.
15+ years of proven experience in compute platform engineering, site reliability, or systems architecture with a focus on automation at massive scale.
Deep expertise in Kubernetes architecture and designing/deploying virtualization architectures, specifically operating VMs inside K8s (KubeVirt, OpenShift).
In-depth knowledge of hardware technologies (GPUs, high-speed backplane networking) with a track record of mitigating hardware-level failures and anomalies.
Experience running large global environments spanning bare metal, virtualized infrastructure, and cloud with a unified GitOps posture (ArgoCD or similar).
Proficiency in programming languages such as Go and/or Python, alongside expert-level infrastructure-as-code development (Terraform, Config Management).
Strong leadership skills with the ability to influence technical direction across highly autonomous teams.
Hands-on experience managing bleeding-edge, pre-release hardware in production environments (preferred).
Ansible Automation Platform
AWX
Salt
Go
Python
Java
Kubernetes
Linux
Containers
CI/CD
Infrastructure as Code
Databricks
Distributed Systems
APIs
Secrets Management
Observability
Kubernetes
Go
Python
Linux
AWS
EKS
Terraform
Argo CD
Helm
Prometheus
Grafana
PyTorch
Ray
vLLM
SGLang
TensorRT-LLM
CUDA
NVLink
NVSwitch
NCCL
EFA
DCGM
Containers
HPC