Manager, Solutions Architecture – Emerging AI Labs

NVIDIA

Solutions Architecture Manager leading NVIDIA GPU, networking, and software teams. Deploying reliable AI infrastructure for strategic customers and emerging AI labs.

Posted 8/10/2026full-timeRemote • California, Colorado, Texas • 🇺🇸 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 Network Systems, with a strong background in Systems Engineering and leadership of technical teams. Proven ability to manage large-scale deployments, mentor engineers, and collaborate with cross-functional teams to drive project success.

Highest-signal resume keywords

GPU And Network Systems ExpertiseLeadership And Mentoring ExperienceSystems Engineering And Debugging SkillsExperience With NVIDIA GPU Systems And SDKsCustomer-Facing Architecture And Field Engineering

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

C/C++ ProgrammingLinux Kernel DevelopmentSystem Software EngineeringCluster Performance TroubleshootingEthernet And InfiniBand NetworkingData Center Infrastructure ManagementVirtualization ConceptsAI Lab Deployment ExperienceDebugging SkillsArchitectural Design

Soft Skills

Excellent Communication SkillsTime ManagementTeam LeadershipMentoringProject Management

Tools & Technologies

NVIDIA SDKsCUDARoCEInfiniBandNICsFabricsData Center ToolsCloud-Native NetworkingPerformance Debugging ToolsDeployment Tools

Industry Keywords

AI NetworkingGPU DeploymentsField EngineeringSystems EngineeringData Center EngineeringSupercomputing EnvironmentsTechnical ReviewsCustomer EngagementStrategic CustomersEmerging AI Labs

Tech Stack

Tools & technologies

CloudLinux

About the role

Key responsibilities & impact

Recruit and manage a team of solutions architects, system/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 GPU and network systems and serve as senior technical contact for strategic customers and emerging AI labs.
Lead compute and network configuration and performance debugging to deliver 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 roadmaps and reference designs.
Expand NVIDIA solution engagements across strategic AI-lab customers.

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 Engineering, Data Center Engineering, or similar roles
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 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
Direct people management and recruiting experience for geographically distributed technical teams
Track record leading bring-up and deployment of large clusters or supercomputing environments
Experience with fast-moving AI labs or frontier-model infrastructure deployments and customer-facing architecture or field engineering 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, RoCE, InfiniBand, and/or ARM-based CPU solutions
Familiarity with virtualization and cloud-native networking concepts
Willingness to travel up to 20% for on-site customer visits and industry events

Benefits

Comp & perks

Equity
Benefits
Remote work locations
Occasional travel opportunities for on-site customer visits and industry events