Senior Software Engineer - Distributed Systems Engineer, EDA Infrastructure

NVIDIA is hiring a Senior Software Engineer to build and scale infrastructure supporting Electronic Design Automation (EDA) workloads. The role focuses on reliable automation and platform services for large GPU- and CPU-based compute systems, including provisioning, monitoring, recovery, and operational improvement.

Responsibilities:

• Design and build platforms that automate the provisioning, configuration, operation, and lifecycle management of large-scale GPU and CPU compute infrastructure
• Develop monitoring, health-management, and remediation systems that improve the 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
• Work with EDA, infrastructure, networking, storage, and hardware engineering teams to deliver scalable solutions for critical chip-design workloads
• Participate in incident response, root-cause analysis, capacity planning, and the continuous improvement of production services

Requirements:

• 5+  years of software engineering or infrastructure engineering experience supporting large-scale production systems
• A BS in Computer Science, Engineering, Physics, Mathematics, or a related field, or equivalent experience
• Strong programming experience in Go or Python, including a solid understanding 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 the ability to work effectively across teams, organizations, and geographic regions
• A systematic approach to problem solving, with a strong sense of ownership and an emphasis on reducing operational toil
• 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
• A 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