Manager, Software Engineering - Networking

Reposted 8 Days Ago
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Santa Clara, CA, USA
In-Office
224K-431K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Manage a US-based software engineering team developing NVIDIA networking products. Responsibilities include debugging complex embedded networking issues, creating diagnostic tools and processes, engaging customers on technical requirements, and collaborating globally with engineers, architects, product managers, and field teams. The role requires embedded networking software expertise, people management experience, strong C and Python skills on Linux, and leadership in AI-native software development.
Summary Generated by Built In

NVIDIA is looking for a creative SW engineering manager to join the team. The incredible growth of AI factories represents the greatest change the world of networking has seen. Spectrum-X is NVIDIA's end-to-end Ethernet Networking solution designed to meet this new challenge with customers including the biggest and fastest-moving organizations in the world. We need a software engineering manager with strong people, customer-facing, and technical skills to join our Spectrum-X engineering team and help make this technology a success.  

What you'll be doing:

  • Building and managing a team of US-based software engineers developing NVIDIA's networking products.

  • Debugging and diagnosing complex networking problems, and crafting the tools/processes to do it better.

  • Engaging directly with NVIDIA customers to ensure we are aligned on their networking requirements and solve their problems.

  • Working with a worldwide team of engineers, architects, product managers, and field personnel.

What we need to see:

  • B.A./B.Sc. in Computer Science or equivalent experience.

  • 8+ overall years of experience developing embedded networking software (e.g. switches, routers, NICs) 

  • 3+ years of experience as a personnel manager leading software teams.

  • Strong programming skills in C and Python on Linux.

  • Leadership in AI-native software development.

  • Outstanding analytical and problem-solving skills, with a keen attention to detail, particularly in identifying and resolving networking issues.

  • Good English communication and interpersonal skills.

  • A track-record of autonomous and successful delivery under challenging conditions.

Ways to stand out from the crowd:

  • Experience of data center network engineering spanning servers, NICs, cabling and switches.

  • Strong understanding of ethernet networking, from switch pipelines (e.g. ACLs, forwarding rules) through networking protocols (like TCP/IP and BGP/EVPN-VxLAN) to network operating systems and their automation.

  • Experience of NVIDIA networking technology such as Bluefield/ConnectX NICs, Spectrum switches, and the Cumulus Linux and SONiC operating systems.

  • Experience recruiting teams of software engineers.

NVIDIA is widely considered to be one of the technology world’s most desirable employers.  We have some of the most forward-thinking and hardworking individuals in the world working for us. If you're creative and autonomous, we want to hear from you.

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
224,000 USD – 356,500 USD for Level 3; and 272,000 USD – 431,250 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 3, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Skills Required

  • Bachelor's degree in Computer Science or equivalent experience
  • 8+ years of experience developing embedded networking software
  • 3+ years of experience as a personnel manager leading software teams
  • Strong programming skills in C and Python on Linux
  • Leadership in AI-native software development
  • Strong analytical and problem-solving skills with attention to networking issues
  • Good English communication and interpersonal skills
  • Track record of autonomous and successful delivery under challenging conditions
  • Data center network engineering experience spanning servers, NICs, cabling, and switches
  • Strong understanding of Ethernet networking, TCP/IP, BGP, EVPN-VXLAN, network operating systems, and automation
  • Experience with NVIDIA BlueField and ConnectX NICs, Spectrum switches, Cumulus Linux, and SONiC
  • Experience recruiting software engineering teams

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility — Feedback suggests equity grants, stock options/RSUs, and a discounted ESPP materially boost total compensation and can deliver significant wealth-building when the stock performs well.
  • Healthcare Strength — Feedback suggests medical, dental, and vision plans with in-network preventive care at 100%, telehealth, and concierge-style support are comprehensive and valued.
  • Parental & Family Support — Feedback suggests up to 22 weeks fully paid parental leave, fertility coverage, and adoption/surrogacy reimbursement provide strong family-focused benefits.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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