Senior Software Engineer - Distributed Systems Engineer, EDA Infrastructure

NVIDIA•Durham, NC

2d•$152,000 - $287,500

About The Position

NVIDIA is hiring a Senior Software Engineer to build and scale infrastructure supporting Electronic Design Automation (EDA) workloads. The role designs reliable automation and platform services for large fleets of GPU- and CPU-based compute systems used by engineering teams. It spans software, operating systems, cluster schedulers, networking, storage, and physical hardware, with a focus on solving operational problems, automating repetitive work, and maintaining reliability as infrastructure grows.

Requirements

At least 5 years of software engineering or infrastructure engineering experience supporting large-scale production systems.
Bachelor’s degree in Computer Science, Engineering, Physics, Mathematics, or a related field, or equivalent experience.
Strong programming experience in Go or Python, including knowledge of data structures, algorithms, testing, and software design.
Experience designing automation for distributed systems and large fleets of Linux-based compute nodes.
Understanding of performance, security, reliability, fault tolerance, state management, and data consistency in complex systems.
Experience with infrastructure automation, software deployment, observability, and operational recovery.
Strong communication skills and ability to work effectively across teams, organizations, and geographic regions.
Systematic problem-solving approach, strong sense of ownership, and emphasis on reducing operational toil.

Nice To Haves

Experience designing or operating large-scale EDA or high-performance computing infrastructure.
Deep knowledge of Linux, GPU and CPU server architecture, networking, storage, and bare-metal lifecycle management.
Hands-on experience with workload schedulers and cluster-management platforms such as Slurm, LSF, Kubernetes, or Bright Cluster Manager.
Experience supporting EDA applications, license-management systems, high-throughput batch workloads, or semiconductor design workflows.
Experience building automated health checks, break-fix remediation, firmware and operating-system upgrade workflows, or node-provisioning systems.
Track record of improving infrastructure reliability, utilization, and recovery time through production-quality automation.
Experience operating infrastructure across multiple data centers or heterogeneous hardware environments.

Responsibilities

Design and build platforms to automate provisioning, configuration, operation, and lifecycle management of large-scale GPU and CPU compute infrastructure.
Develop monitoring, health-management, and remediation systems to improve reliability, availability, and utilization of EDA compute environments.
Automate hardware deployment, operating-system configuration, firmware and software updates, cluster enrollment, and recovery workflows.
Build reliable services and workflows that integrate with workload schedulers, infrastructure management systems, and observability platforms.
Use hardware diagnostics, operating-system signals, scheduler data, and network and storage telemetry to identify failures and return unhealthy systems to service.
Collaborate with EDA, infrastructure, networking, storage, and hardware engineering teams on scalable solutions for critical chip-design workloads.
Participate in incident response, root-cause analysis, capacity planning, and continuous improvement of production services.