Manager, Solutions Architecture – AI Labs

NVIDIA

NVIDIA manager leading architects and engineers deploying GPU, networking, and software infrastructure. Guiding large-scale AI clusters for strategic customer data centers.

Posted 8/10/2026full-timeRemote • California, Texas, Washington • 🇺🇸 United StatesSeniorLead💰 $224,000 - $356,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in GPU and AI networking deployments, with a strong background in systems engineering, project management, and team leadership. Capable of guiding technical discussions, managing customer relationships, and delivering high-quality solutions in complex environments.

Highest-signal resume keywords

GPU And AI Networking ExpertiseSystems Engineering And Debugging SkillsTeam Leadership And MentoringData Center Networking ExperienceCustomer-Facing Communication

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

C/C++ ProgrammingLinux Kernel DevelopmentSystem Software ExpertiseCluster Performance TroubleshootingNVIDIA GPU SystemsCUDA SDKInfiniBand NetworkingEthernet NetworkingVirtualization ConceptsCloud-Native Networking

Soft Skills

Time ManagementCommunication SkillsMentoring AbilitiesProject Management

Tools & Technologies

NVIDIA Networking TechnologiesNICsRoCEData Center Infrastructure ToolsDebugging Tools

Industry Keywords

AI InfrastructureSupercomputing EnvironmentsField EngineeringData Center EngineeringElectrical EngineeringComputer Science

Tech Stack

Tools & technologies

CloudLinux

About the role

Key responsibilities & impact

Recruit and manage a team of solutions architects, systems/network engineers, and software engineers focused on large-scale GPU and AI networking deployments.
Set priorities, allocate resources, mentor team members, and ensure high-quality customer delivery across concurrent projects.
Participate directly in technical reviews, design decisions, and critical debugging efforts.
Provide subject-matter expertise in advanced GPU and network systems as senior technical contact for a strategic AI lab.
Lead compute and network configuration and performance debugging for reliable clusters.
Guide compute, network, and software architecture discussions and support server, network, and cluster bring-up, including on-site data center work where needed.
Collect and synthesize customer-specific requirements.
Partner with GPU and Network Systems Engineering, Product Management, and Sales to influence roadmap priorities and package reference designs and solutions.
Partner with customer engineering and security stakeholders to understand security requirements and translate them into scalable AI infrastructure.
Lead customer meetings, communicate status and risks, and produce design documents, debug summaries, and presentations.

Requirements

What you’ll need

BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or another Engineering field, or equivalent experience.
8+ years of experience in Systems/Solutions/Field Engineering, Network or Data Center Engineering, or similar roles.
2+ years leading or mentoring engineers or architects.
Direct people management and recruiting experience for geographically distributed technical teams.
System-level expertise across CPU/GPU server architecture, NICs, Linux, system software, and kernel drivers.
Experience with data center networking, including Ethernet and/or InfiniBand switches, NICs, fabrics, associated tooling, and cluster performance troubleshooting.
Familiarity with data center infrastructure, including power, cooling, and deployment constraints.
Ability to lead technical teams, set priorities, and drive complex projects from design through production.
Experience working with Product Management, Sales, and Engineering.
Strong time management and ability to balance planning with hands-on support.
Excellent written and verbal communication, including customer meetings, status and risk communication, design documents, debug summaries, and presentations.
Track record leading bring-up and deployment of large clusters or supercomputing environments.
Background working with AI labs or frontier-model infrastructure deployments and customer-facing roles.
Systems engineering, coding, and debugging skills, including C/C++, Linux kernel, and drivers.
Hands-on experience with NVIDIA GPU systems and SDKs such as CUDA, NVIDIA networking technologies such as NICs, RoCE, or InfiniBand, and/or ARM-based CPU solutions.
Familiarity with virtualization and cloud-native networking concepts.
Ability to travel occasionally, up to 20%, for on-site customer visits and industry events.

Benefits

Comp & perks

Equity
Benefits
Remote work locations
NVIDIA uses extensive conferencing tools
Occasional travel up to 20% for on-site customer visits and industry events