Nvidia Principal Infrastructure SRE - Compute 

United States, Texas 

470960577

What you will be doing:

• Lead initiatives to transform IT Compute platform architecture to build new service offerings across On-Prem & Cloud.

• Define and implement metrics to measure the efficiency of compute platforms & services and drive efficiency.

• Collect and review system data for capacity and planning purposes, analyze capacity data and develop plans for appropriate level enterprise-wide systems, and coordinate with management personnel in implementing changes.

• Develop and maintain tools for collecting, analyzing, and visualizing data for reporting, alerting, monitoring.

• Collaborate with NVIDIA leadership, senior engineers, program managers, and product managers to develop compelling IT products and services that meet customer needs.

What we need to see:

• Bachelor’s degree in Engineering, Computer Science, Mathematics, or related field, or equivalent experience

• 12+ years of proven experience in compute platform engineering with a focus on automation.

• Experience with design and deployment of virtualization architectures, including VMware, Openshift or KubeVirt platforms.

• Proven experience evaluating existing application architectures and identify opportunities for containerization to improve scalability, reliability, and efficiency.

• Strong analytical skills with the ability to define and track key performance metrics.

• Experience in developing tools for data analysis and performance profiling, Development with Terraform, Config Management tools.

• Proficiency in programming languages such as Go and/or Python.

• Experience with running large environments consisting of BareMetal, large scale virtualized environment with a mix of tens of thousands of VM’s and cloud infrastructure.

Ways to stand out from the crowd:

• Deep understanding of other infrastructure components like Storage, DNS, AD, Security Tools etc..

• Hands-on experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.

• Solid understanding of microservices architecture, infrastructure as code (IaC) and configuration management tools.

• Understanding of AI ops and how to leverage LLMs to automate various optimization initiatives