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NVIDIA

Designs the chips and software that power AI

Network Software Engineer - Automation and Intelligence

Network Engineering & AdministrationConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • A master's degree in Computer Science, Engineering, or a related field, or equivalent experience.
  • At least 12 years of experience in network engineering or network software, including both build and production operations.
  • Hands-on network automation experience, such as Python, Ansible, REST, gNMI, NETCONF APIs, and Git-based workflows.
  • Grounding in routing, switching, and network architecture, including BGP, OSPF, EVPN/VXLAN, and MLAG.
  • Experience with multi-vendor environments, such as Arista, Cisco, Cumulus/NVIDIA, Palo Alto, and similar vendors.
  • Experience managing complex projects from start to finish.

Responsibilities

  • Design and implement network automation for new builds and bring-ups, including zero-touch provisioning, configuration generation, validation, and handoff to operations.
  • Support live networks with automated change execution, health checks, drift detection, and incident triage; identify and fix issues before they affect service levels.
  • Contribute to the source of truth, CI/CD pipelines, orchestration, and observability integrations used by the automation platform.
  • Build LLM- and agent-based network tooling that progresses from read-only investigation to autonomous, self-validating change execution as each change class proves safe, with rollback, scoped boundaries, and full audit trails.
  • Partner with network, compute, storage, and facilities teams to turn operational difficulties into reliable, reusable software.
  • Document, mentor, and enable other engineers to contribute to automation beyond the core team.

Desired Qualifications

  • Experience implementing LLM- or agent-based tooling in operations with robust oversight, including read-only restrictions, approval processes, and audit logs.
  • Working knowledge of agent frameworks, MCP, RAG, and applying machine learning to telemetry or capacity analysis.
  • Familiarity with incident management and change platforms such as BigPanda and ServiceNow, and source-of-truth tooling such as Nautobot and NetBox.
  • Background in cybersecurity and network security practices.
  • Experience with large-scale GPU/AI fabrics, InfiniBand, RoCE, or other high-performance networks.
  • Clear communication skills and a focus on maintaining an inclusive, collaborative team culture.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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