Senior Software Engineer, Platform Engineering - EDA Infrastructure

Details

NVIDIA is hiring engineers to build and operate the governed infrastructure platform behind its Electronic Design Automation (EDA) and hardware engineering organization. The platform provides engineering teams with a self-service path from source code to production across cloud environments and physical sites. The role requires strong programming skills, a deep understanding of distributed systems, and experience operating large-scale production infrastructure.

The ideal candidate is comfortable across the cloud-native stack, from Kubernetes to cluster schedulers. They use existing open-source solutions where appropriate and build platform capabilities once for all teams to use. The role focuses on solving complex operational problems, replacing manual handoffs with self-service, improving developer experience, and maintaining reliability as the infrastructure fleet and number of onboarded teams grow.

Responsibilities

• Own the lifecycle of Kubernetes clusters, including control planes, node lifecycles, fleet-wide upgrades, bare-metal provisioning, storage, and networking.
• Build self-service capabilities for compute, secrets, certificates, DNS, access, and deployment.
• Extend Kubernetes with controllers and operators, using open-source projects where appropriate and developing custom solutions when needed.
• Own CI/CD pipelines and shared platform services, including policy, autoscaling, and observability.
• Onboard new teams and sites onto the platform through repeatable processes, self-service tooling, readiness requirements, and documentation.
• Work with EDA, infrastructure, networking, storage, and hardware engineering teams to deliver scalable solutions for critical chip-design workloads.
• Participate in on-call duties, incident response, root-cause analysis, and capacity planning.

Requirements

• 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 data structures, algorithms, testing, and software design. Go is the primary and preferred language; deep experience in another systems language may also be applicable.
• Production experience operating Kubernetes or a comparable large-scale platform, such as an internal developer platform or another cluster manager, with hands-on ownership of clusters and components.
• Experience building automation that makes decisions and takes action on distributed infrastructure, including reconciliation loops, controllers, operators, or self-healing remediation systems.
• Understanding of performance, security, reliability, fault tolerance, state management, and data consistency in complex systems.
• Experience onboarding or migrating teams onto new infrastructure using self-service tooling, readiness checks, and documentation.
• Strong communication, systematic problem-solving, ownership, and operational-toil reduction skills.

Preferred Qualifications

• Contributions to open-source infrastructure projects.
• Experience running Kubernetes on bare metal with Cluster API, Metal3, Ceph, or Cilium.
• Experience with EDA applications, license-management systems, high-throughput batch workloads, or semiconductor design workflows.
• Experience writing Kubernetes operators or working with cloud-native technologies such as cert-manager, external-dns, Argo CD, or Kyverno.
• Experience improving infrastructure reliability, utilization, and recovery time through production-quality automation.
• Experience operating infrastructure across multiple data centers or heterogeneous hardware environments, both on premises and in the cloud.

Benefits

• Equity and employee benefits are provided.
• NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.

Applications will be accepted at least until November 14, 2026.