Senior Software Manager, AI Networking

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1 · Remote

Senior Manager for AI Networking group at NVIDIA, leading a customer-focused engineering team. Responsibilities include people leadership, technical guidance on networking technologies (BlueField, ConnectX, Spectrum-X, DOCA, RDMA, RoCE, InfiniBand), supporting customer deployments of AI systems, translating field requirements into product improvements, and building team capability. The role emphasizes scaling impact through others and operational excellence.

What you'd actually do

  1. Lead, support, and grow a high-performing team of customer-facing networking engineers.
  2. Provide organizational and technical leadership across NVIDIA networking technologies, including BlueField, ConnectX, Spectrum-X, DOCA, RDMA, RoCE, and InfiniBand.
  3. Support large-scale customer design-in, bring-up, and deployment of current and next-generation AI systems, while preparing for future platforms.
  4. Engage directly with engineering, product management, architecture, and program teams to translate field requirements into product improvements and roadmap priorities.
  5. Build team capability through hiring, onboarding, coaching, mentoring, and performance management.

Skills

Required

  • BS, MS, or PhD in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
  • 12+ overall years of experience in software, systems, networking, or AI infrastructure engineering.
  • 5+ years of proven experience leading and scaling engineering teams, including hiring, mentoring, and managing senior engineers or technical leads.
  • Strong technical background in networking and distributed systems, with an understanding of RoCE, InfiniBand, L1-L4 networking fundamentals, and large-scale system behavior.
  • Experience handling customer issues and driving alignment across teams in fast-paced, high-visibility situations.
  • Strong communication skills, with the ability to work effectively with customers, engineering, product, architecture, and leadership teams.
  • Demonstrated ability to scale impact through others and build strong team execution.
  • Ability to operate effectively across organizational and geographic boundaries in dynamic environments.

Nice to have

  • Experience leading customer-facing engineering teams supporting hyperscalers, cloud providers, or large-scale AI factory deployments.
  • Familiarity with technologies such as DOCA, DPDK, RDMA verbs, NCCL, CUDA-aware networking, congestion control, and telemetry or performance tuning at scale.
  • Experience leading multi-functional initiatives across multiple teams, sites, or time zones.
  • Established record of improving operational excellence, triage efficiency, and engineering productivity via automated and AI-enhanced workflows.
  • Experience growing team scope, hiring strong talent, and building the foundation for future organizational growth.

What the JD emphasized

  • customer-centered engineering team
  • large-scale AI infrastructure initiatives
  • hyperscalers, cloud providers, and AI factory environments
  • customer demands and platform complexity
  • customer-focused engineering team
  • broad AI infrastructure efforts
  • customer issues
  • fast-paced, high-paced situations
  • customer-facing engineering teams
  • large-scale AI factory deployments
  • AI-enhanced workflows