Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
API
AWS @ 4
ArgoCD @ 4
GCP @ 4
GPU
Go @ 6
Kubernetes @ 6
Leadership @ 7
Mathematics @ 4
Microservices @ 4
Networking @ 4
OpenShift @ 6
Python @ 6
Terraform @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA has been reinventing computer graphics, PC gaming, and accelerated computing for 30 years. Today, we’re tapping into the unlimited potential of AI to define the next era of computing.
We are seeking a highly skilled Principal Software Engineer to join our dynamic team to drive efficiency, define platform architecture, and optimize the performance of our infrastructure both on-prem and in the cloud.
What You Will Be Doing:
Responsibilities
- 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. 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. 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 critical migration of massive legacy workloads—including large-scale, long-running VDI environments—into modern Kubernetes orchestration.
Requirements
- 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.
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.
Base salary range: 248,000 USD - 391,000 USD. You will also be eligible for equity and benefits.
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