Senior Software Developer

About the role

NVIDIA is looking for a Senior Software Engineer to join NSV tools (Network Solutions Validation) group. Our group builds the data and analytics platform behind NVIDIA’s networking validation, processing large-scale test results, telemetry and cluster health data from some of the world’s largest AI and HPC data centers. As a senior team member, you will be developing services that turn this data into insights, accelerating the velocity and reliability of the validation process. You will work with NIC, OS, Switch, HCA, CPU and GPU compute as well as architects, network engineers, and developers. With dedicated engineers around the globe, the work environment is dynamic, impactful, and fast-paced. Are you ready for the challenge?

What you’ll be doing:

- Owning features end to end, from problem definition through design, delivery and production.

- Collaborating closely with networking, data and performance architects, validation engineers, DevOps and data teams to understand requirements and deliver robust solutions.

- Leading the development of scalable services that analyze large-scale validation test results and improve visibility into cluster health KPIs across HPC data centers.

- Leading the development of AI-driven and agent-based features that improve usability, observability, and debuggability.

- Leading the deployment and operation of services on Kubernetes (K8s) with Docker and containerized environments.

- Troubleshooting issues in distributed environments and improving HPC data center health observability.

- Taking an active part in leading the team’s development process and driving its continuous improvement.

- Mentoring engineers and rapidly growing the group’s knowledge across technical areas.

What we need to see:

- B.Sc. in Computer Science or a related field (or equivalent experience).

- 5+ years of hands-on software development experience with strong Python proficiency.

- Strong understanding of software design patterns and architecture in large-scale networked systems.

- Hands-on experience with Docker, containers, Kubernetes and microservices architectures.

- Strong debugging and problem solving capabilities in distributed systems or multi-node environments.

- Hands-on experience with agentic AI development tools and using agentic workflows to solve real-world problems.

- Proven track record of turning loosely defined problems into well-scoped, delivered solutions.

- Ability to work independently and drive measurable impact, with excellent communication skills and a strong sense of ownership.

Ways to stand out from the crowd:

- Experience with big data and large-scale systems, including leading the architecture and design of complex distributed systems.

- Experience with data engineering, data analysis and streaming data collection (e.g., SQL, pandas, ETL pipelines, Kafka, gRPC, gNMI).