Network Software Engineer, Automation and Intelligence

NVIDIA•Santa Clara, CA

23h

About The Position

NVIDIA is hiring a Network Software Engineer for its Network Automation & Intelligence Platforms team. The role builds and operates network automation systems across corporate offices, campuses, HPC data centers, contract manufacturing sites, and labs. The engineer will develop automation for network builds and production operations, contribute to the platform stack, integrate AI-enabled tooling with appropriate safeguards, and collaborate across technical teams to improve and scale automation.

Requirements

MS in Computer Science, Engineering, or a related field, or equivalent experience.
12+ years of experience in network engineering or network software, including both network builds and production operations.
Hands-on network automation experience, such as Python, Ansible, REST/gNMI/NETCONF APIs, and Git-based workflows.
Solid grounding in routing, switching, and network architecture, including BGP, OSPF, EVPN/VXLAN, and MLAG.
Experience in multi-vendor environments, such as Arista, Cisco, Cumulus/NVIDIA, and Palo Alto.
Strong problem-solving abilities and a history of managing complex projects from start to finish.

Nice To Haves

Experience implementing LLM- or agent-based operational tooling with robust oversight, including read-only restrictions, approval processes, and audit logs.
Working knowledge of agent frameworks, MCP, RAG, and applying ML to telemetry or capacity analysis.
Familiarity with incident management and change platforms such as BigPanda and ServiceNow, and source-of-truth tools 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.

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 through automated change execution, health checks, drift detection, and incident triage; identify and resolve issues before they affect service levels.
Contribute to the source of truth, CI/CD pipelines, orchestration, and observability integrations that support automation.
Build LLM- and agent-based network tools that can progress from read-only investigation to autonomous, self-validating change execution when proven safe, with rollback, scoped boundaries, and audit trails.
Partner with network, compute, storage, and facilities teams to turn operational challenges into reliable, reusable software.
Document automation, mentor others, and enable engineers outside the core team to contribute.