NVIDIA
Manager, First Time Deployment - NVIS
$184K–$345K
US, CA, Santa Clara · Manager · Full-time · Posted Sep 29, 2026
- Experience
- 8+ overall years, with 2+ years leading or mentoring engineers or architects.
- Education
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or other Engineering fields, or equivalent experience.
About the job
Leads a technical team deploying NVIDIA GPU and AI networking systems, taking solutions from prototype through customer-site bring-up, validation, debugging, and production deployment.
What you'll do
- Recruit, manage, mentor, and allocate work for engineers and architects across concurrent customer deployments.
- Lead technical reviews, architecture discussions, cluster bring-up, and complex compute/network performance debugging.
- Gather customer requirements and collaborate with engineering, product management, and sales to inform roadmaps and identify deployment opportunities.
What they ask for
- BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or another Engineering field, or equivalent experience.
- 8+ overall years in Systems/Solutions/Field Engineering, Network or Data Center Engineering, or similar roles, including 2+ years leading or mentoring engineers or architects.
- System-level expertise across CPU/GPU server architecture, NICs, Linux, system software, and kernel drivers.
- Experience with data center networking (Ethernet and/or InfiniBand switches, fabrics, and associated tooling) and familiarity with data center infrastructure.
Nice to have
- Direct people management and recruiting experience for geographically distributed technical teams; experience bringing up and deploying large clusters or supercomputing environments.
- Customer-facing field engineering, escalation, or pre/post-sales architecture experience; systems coding and debugging skills, including C/C++, Linux kernel, and drivers.
Pay
184,000 USD - 287,500 USD base salary; 216,000 USD - 345,000 USD base salary
Tools
CPU/GPU, NICs, Linux, kernel drivers, Ethernet, InfiniBand, C/C++, CUDA
AI focus
Deploys AI Factory infrastructure and GPU-accelerated systems for customer AI applications.
Model-written summary · the original posting is authoritative