> Markdown version of [/jobs/ext/3954229-principal-software-engineer-compute-infrastructure](https://www.wearedevelopers.com/jobs/ext/3954229-principal-software-engineer-compute-infrastructure). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Principal Software Engineer - Compute Infrastructure

- **Company:** NVIDIA Corporation
- **Location:** Santa Clara, CA, United States
- **Salary:** $248,000.0
- **Contract:** Permanent contract
- **Skills:** OpenTofu, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Computing Platforms, Cloud Computing, Computer Programming, Python (Programming Language), Network File Systems, OpenShift, Performance Tuning, Reliability Engineering, Software Engineering, Systems Architecture, Transmission Control Protocol (TCP), Virtualization Technology, AI Infrastructure, Graphics Processing Unit (GPU), Multi-Cloud, Kubernetes, Information Technology, Bare Metal, Hardware Infrastructure, Software Coding, Model Inference, Terraform, Nvme, Microservices
- **Published:** October 27, 2026
- **Apply:** https://www.careerbuilder.com/job-details/principal-software-engineer-compute-infrastructure-santa-clara-ca--f9bc2bd2-fa01-4074-ba9b-961d8f7a66d2

## About the Role

Software Engineering, Computer Software, Autonomous Driving Systems, GPU (Graphics Processing Unit), Artificial Intelligence (AI), Software Engineering, Architectural Services, Cloud Computing, Performance Tuning/Optimization, Enterprise Computing, * Bachelor's degree in Engineering, Computer Science, Mathematics, or related field, or equivalent experience.

 * 15+ years of proven experience in compute platform engineering, site reliability, or systems architecture with a heavy 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, silent data corruption, and anomalies in large-scale environments.
 * 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 without relying on top-down mandates.

Ways To Stand Out From The Crowd:

 * Hands-on experience managing bleeding-edge, pre-release hardware in production environments.
 * Deep understanding of advanced storage migrations and protocols (NFSv4, NVMe/TCP, Hyperconverged storage).
 * Solid understanding of microservices architecture and seamless multi-cloud deployment strategies (AWS, GCP).
 * Proven track record of building "Day 2" operational maturity (self-service, advanced auto-remediation, strict SLAs) from the ground up on existing foundations.

## Description

We are seeking a highly skilled Principal Software Engineer to join our dynamic team. Our company is at the forefront of technological innovation, and we are dedicated to driving efficiency, defining platform architecture, and optimizing the performance of our infrastructure both on-prem and in the cloud. You will lead the architectural vision for a massive global platform and spearhead the operationalization of our internal frontier-class AI inference systems. Join us in this exciting endeavor!

What You Will Be Doing:

 * Define Platform Architecture: Lead initiatives to architect and transform our global enterprise compute platform-running thousands of nodes and tens of thousands of VMs and containers via OpenShift and KubeVirt-by defining service tiers, SLAs, and automated cluster lifecycles.
 * Operationalize Frontier AI Infrastructure: Build the operational foundation for our internal AI inference platform scaling to frontier-class models. You will develop automated remediation pipelines, hardware watchdogs, and telemetry for pre-release, rack-scale GPU systems (including Blackwell and upcoming architectures).
 * Drive Strategic Capacity & Scale: Collect and review system data for capacity planning to navigate extreme hardware supply constraints. Develop proactive strategies, including public cloud bursting, hardware dogfooding, and evaluating alternative compute architectures (e.g., ARM).
 * Build the "Paved Road": Collaborate with highly autonomous NVIDIA engineering teams to drive cultural adoption of standard platforms. You will design compelling self-service architectures, APIs, and Terraform/OpenTofu providers that teams want to use.
 * Lead Complex Migrations: Evaluate existing application architectures and drive the fraught but critical migration of massive legacy workloads-including large-scale, long-running VDI environments-into modern Kubernetes orchestration.