Manager, Solutions Architecture - GPU and Networking Systems

Nvidia

Confirmed live today High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CATXCOCA
Salary: $224,000–$356,500 / yr
Posted: 3 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $226k

This role $290k

$163k most similar roles pay here $377k

This role pays more than 92% of similar roles. Most pay $196,750–$255,075 — the shaded band above. At the midpoint, this role pays about $290k versus about $226k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 879 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 859 roles with salary data.

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At a glance

TL;DR · Manager, Solutions Architecture - GPU and Networking Systems

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Manager, Solutions Architecture – GPU and Networking Systems leads a team of solutions architects, system/network, and software engineers focused on large-scale GPU and AI networking deployments. This role involves recruiting and managing staff while providing technical leadership for end-to-end solution designs, debugging, and production deployments in customer data centers. The manager serves as a senior technical point of contact, overseeing complex compute and network configuration, performance debugging, and cluster bring-up. Key responsibilities include synthesizing customer requirements to influence product roadmaps and collaborating with engineering and sales teams. Required expertise includes CPU/GPU server architecture, NICs, Linux, system software, kernel drivers, and data center networking using Ethernet or InfiniBand fabrics. Candidates should possess skills in C/C++, CUDA, RoCE, and ARM-based solutions while navigating infrastructure constraints like power and cooling to deliver performant, reliable clusters for AI applications.

Skills

GPU CUDA InfiniBand Ethernet RoCE Linux C++ C Kernel Drivers System Software Data Center Networking ARM Virtualization Cloud-native Networking Supercomputing

What you'll do

Recruit, manage, and mentor a team of solutions architects and engineers focused on large-scale GPU and AI networking deployments.
Lead technical reviews, design decisions, and deep-dive debugging for complex compute and network configurations.
Serve as the senior technical point of contact and trusted advisor for strategic customers.
Oversee server, network, and cluster bring-up, including performing on-site data center work when necessary.
Synthesize customer requirements to influence product roadmap priorities and reference design packaging.
Identify new project opportunities for NVIDIA products in data center and AI applications.
Coordinate with internal engineering, product management, and sales teams to ensure high-quality customer delivery.

What we're looking for

BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or another engineering field or equivalent experience.
Experience in Systems, Solutions, Field Engineering, Network, or Data Center Engineering roles.
2+ years of experience leading or mentoring engineers or architects as a manager or technical lead.
System-level expertise in CPU/GPU server architecture, NICs, Linux, system software, and kernel drivers.
Experience with data center networking including Ethernet and InfiniBand switches, fabrics, and associated tooling.
Familiarity with data center infrastructure such as power, cooling, and deployment constraints.
Proven ability to lead technical teams, set priorities, and manage projects from design through production.
Excellent communication skills for leading customer meetings and producing technical documentation.
Experience with recruiting and managing geographically distributed technical teams (preferred).
Track record of bringing up and deploying large clusters or supercomputing environments (preferred).
Background in external customer-facing roles such as field engineering or pre/post-sales architecture (preferred).
Coding and debugging skills including C/C++, Linux kernel, and drivers (preferred).
Hands-on experience with NVIDIA GPU systems, SDKs, networking technologies, or ARM-based CPU solutions (preferred).

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