$248,000 – $391,000
Listed on NVIDIA’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
Lead the design and evolution of NVIDIA's enterprise infrastructure automation and configuration management platforms across data centers and cloud environments. This is a hands-on architecture role for someone with deep systems engineering expertise who can set multi-year technical direction, mentor senior engineers, and drive large-scale transformations from strategy through production adoption.
Our summary, not NVIDIA’s wording. The full posting is on their site.
Skills this role names
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What they ask for
Required
- 15+ years of progressive software engineering experience with complex, business-critical platforms and distributed systems
- Bachelor's or Master's degree in Computer Science, Engineering, or equivalent experience
- Deep knowledge of enterprise configuration management or infrastructure automation platforms like Ansible, AWX, or Salt
- Deep hands-on expertise in Go, Python, Java, or comparable systems programming language including APIs, concurrency, and distributed systems
- Strong hands-on experience in Linux, Kubernetes, containers, cloud and hybrid infrastructure, and CI/CD
- Strong experience with enterprise data and automation pipelines using Databricks or comparable platforms
- Proven experience defining and evolving architecture of large-scale infrastructure platforms across multiple teams and environments
- Demonstrated ability to identify organization-wide challenges, establish strategy, and drive cross-team implementation
- Outstanding communication and technical leadership skills with ability to influence senior leaders and mentor experienced engineers
Nice to have
- Experience architecting, deploying, and managing Ansible Automation Platform at enterprise scale
- Experience developing platforms managing large global infrastructure fleets across data centers, public clouds, compute, storage, and networking
- History of leading development and enterprise-wide adoption of AI-enabled configuration management or autonomous operations platform
- Experience using AI to solve infrastructure challenges like configuration drift, compliance, change-risk analysis, incident diagnosis, or automated remediation