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NVIDIA

Designs the chips and software that power AI

Senior Manager - Software Engineering, Rack Scale Systems Infrastructure

Engineering LeadershipConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's, master's, or doctoral degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field, or equivalent experience.
  • At least 12 years of overall engineering experience in systems software, platform software, server firmware, or data center infrastructure, including at least 6 years managing software or firmware engineering teams.
  • A track record of delivering production software across multiple programs in a matrix organization while aligning shared resources and dependencies and maintaining quality, release rigor, and effective production support.
  • A solid technical background in Linux, distributed systems, application programming interfaces, state machines, and failure handling.
  • Familiarity with data center architecture, hardware-conscious orchestration, server manageability, firmware or operating system lifecycle, telemetry, and large-scale reliability.
  • Software development experience in Go, C++, or Rust, with the ability to review designs and code, guide debugging, and assess engineering quality.
  • The ability to guide distributed engineering groups, recruit and nurture engineers, cultivate technical leaders, assign significant responsibilities, and maintain a steady standard of performance.
  • Clear written and verbal communication, good judgment under ambiguity, and experience aligning engineering teams, customers, and partners on practical solutions.

Responsibilities

  • Own delivery of rack-scale infrastructure software in a cross-functional organizational structure, coordinating commitments, addressing ownership gaps, and remaining accountable from requirements through production adoption and support.
  • Translate business needs and evolving hardware roadmaps into release priorities and achievable plans, balancing staffing, dependencies, and technical risk as priorities change.
  • Partner with architects and technical leads on control planes, lifecycle orchestration, health analysis, and recovery; guide engineering tradeoffs and ensure reliability, security, and maintainability.
  • Build and develop the team through hiring, mentoring, and clear performance expectations; grow technical leads and future managers, delegate important ownership, and balance work across the team.
  • Establish planning, validation, release, and issue triage practices; use delivery and quality evidence to identify risks, drive root-cause resolution of production issues, and improve team practices.
  • Coordinate with firmware, platform, networking, quality assurance, security, and operations teams to deliver capabilities; work with customers and partners to turn deployment feedback into product improvements.
  • Own the team's open-source delivery and support practices, including contribution review, issue triage, documentation, and release maintenance.
  • Communicate priorities, progress, and tradeoffs to engineers, collaborators, and leadership; make decisions under ambiguity and carry cross-team commitments through to completion.

Desired Qualifications

  • Experience across the rack-scale systems lifecycle, from hardware bring-up and validation through provisioning, firmware and operating system updates, production operations, and recovery.
  • Familiarity with NVIDIA GB200 or GB300 systems.
  • Experience with Kubernetes controllers or operators, declarative control planes, and simulation or fault injection to validate software before hardware is available.
  • Hands-on experience with baseboard management controller software, OpenBMC, embedded Linux, Python, and server debugging.
  • Familiarity with Redfish or related standards for out-of-band management and device security, and with accelerated computing platforms using NVLink, Ethernet, or InfiniBand.
  • Experience building open-source infrastructure software used by external teams, strong Rust experience, and thoughtful use of artificial intelligence tools for development, testing, and debugging.

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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