Manager, Solutions Architecture – AI Labs

Job not on LinkedIn

🔥 0 minutes ago

🏄 California, Texas, +1 more states – Remote

🏄 California – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $224k - $356.5k / year

⏰ Full Time

🟠 Senior

🔴 Lead

💻 Solutions Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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

• 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

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