Senior Software Architect, Observability Platform

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4 Locations
In-Office or Remote
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role

NVIDIA’s Infrastructure organization is seeking a Senior Software Architect for our Observability Platform to architect and implement distributed observability systems for data centers enabling EDA workflows. We serve and collaborate directly with NVIDIA’s rapidly growing HW, and SW engineering teams across the company. You will be working with a team of dedicated engineers on systems for data collection, aggregation, enrichment, storage, retrieval, and visualization to spectacularly improve efficiency, performance, and productivity of EDA workloads. You will develop, deploy, and operate observability solutions for multiple CPU and GPU compute clusters around the world. 

What You’ll Be Doing: 

  • Collaborate with HW, and SW engineering teams to deliver observability solutions that meet their needs in EDA clusters. 

  • Develop, test, and deploy data collectors, pipelines, visualization and retrieval services. 

  • Define data collection and retention policies to balance network bandwidth, system load, and storage capacity costs with data analysis requirements. 

  • Work in a diverse team to provide operational and strategic data to empower our engineers and researchers to improve performance, productivity, and efficiency. 

  • Continuously improve quality, workloads, and processes through better observability. 

What We Need to See: 

  • Experience developing large scale, distributed observability systems. 

  • Ability to collaborate with data scientists, researchers, and engineering teams to identify high value data for collection and analysis. 

  • Experience with turning raw data into actionable reports 

  • Experience with observability platforms such as Apache Spark, Elastic/Open Search, Grafana, Prometheus, and other similar open-source tools 

  • Python programming experience and use of API calls 

  • Passion for improving the productivity of others 

  • Excellent planning and interpersonal skills 

  • Flexibility/adaptability working in a dynamic environment with changing requirements 

  • MS (preferred) or BS in Computer Science, Electrical Engineering, or related field or equivalent experience.

  • 8+ years of proven experience. 

Ways To Stand Out from The Crowd: 

  • Background in computer science, EDA software, open-source software, infrastructure technologies, and GPU technology. 

  • Prior experience in infrastructure software, production application software development, software development, release and support methodology and DevOps 

  • Experience in the management of datacenters and large-scale distributed computing 

  • Experience working with EDA developers 

  • Consistent track record of driving process improvements and measuring efficiency and a passion for sharing knowledge and experience driving complex projects end-to-end. 

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until January 13, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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