Senior Solutions Architect – AI Infrastructure, Enterprise ISVs

🕒 July 16

🏄 California, New York, +2 more states – Remote

🏄 California – Remote 🗽 New York – Remote 🤠 Texas – Remote ☕ Washington – Remote

💵 $184k - $287.5k / year

⏰ Full Time

🟠 Senior

💻 Solutions Engineer

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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

• Partner with ISVs on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and production deployment guidance • Advise on the design, build-out, and optimization of accelerated AI infrastructure, including large-scale clusters • Support infrastructure design across compute, networking, storage, containers, observability, security, power, and data center operations • Drive adoption of systems monitoring, telemetry, and management tools to improve cluster utilization, reliability, performance and workload insight • Build repeatable reference architectures, deployment guides, sizing guidance, benchmark reports, technical playbooks, demos and whitepapers • Travel up to 20% customer meetings may be required

🎯 Requirements

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience) • 8+ years of hands-on experience in AI infrastructure, accelerated computing, distributed systems, cloud infrastructure, high-performance computing, or machine learning platforms • Strong experience designing, deploying, and operating accelerated computing infrastructure at scale • In-depth knowledge of AI cluster orchestration, scheduling, automation and CI/CD deployment pipelines • Understanding of data center networking technologies such as InfiniBand, Ethernet, RDMA, network configuration or performance tuning • Familiarity with infrastructure requirements for AI workloads, including distributed training, inference serving, model deployment, storage performance, and cluster reliability • Excellent presentation, communication, problem-solving, documentation, and collaboration skills.

🏖️ Benefits

• You will also be eligible for equity and benefits.