Solutions Architect, AI Infrastructure

at Nvidia
📍 Santa Clara, United States
USD 148,000-235,800 per year
MIDDLE SENIOR
✅ Remote

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Docker @ 3 Kubernetes @ 3 Linux @ 3 DevOps @ 3 MLOps @ 3 Communication @ 3 Networking @ 3 Product Management @ 3 Debugging @ 3 CUDA @ 3 GPU @ 3

Details

NVIDIA is looking for an experienced systems and network infrastructure Solutions Architect Engineer. This role focuses on bringing new Artificial Intelligence (AI) hardware and software technologies to production, supporting accelerated computing applications.

Responsibilities

  • Work with NVIDIA Consumer Internet and IT Services customers on data center GPU server and networking infrastructure deployments as a solution architect.
  • Guide customer discussions on network topologies, compute/storage, and support bring-up of server/network/cluster deployments, including visiting customer data centers during the bring-up phase.
  • Identify new project opportunities for NVIDIA products and technology solutions in data center and artificial intelligence applications.
  • Collaborate closely with Systems/Network Engineering, Product Management, and Sales teams.
  • Act as a trusted advisor to customers through regular technical meetings covering product roadmap, cluster debugging, feature discussions, and technology introductions.
  • Build custom product demonstrations and POCs addressing critical business needs.
  • Analyze and debug compute/network performance issues.

Requirements

  • BS/MS/PhD in Electrical/Computer Engineering, Computer Science, Physics, or related fields, or equivalent experience.
  • 5+ years of Solution Engineering or similar engineering roles experience.
  • System-level understanding of server architecture, NICs, Linux, system software, and kernel drivers.
  • Practical knowledge of networking including switching & routing for Ethernet/Infiniband, and data center infrastructure (power/cooling).
  • Knowledge of DevOps/MLOps technologies such as Docker/containers, Kubernetes.
  • Effective time management and multitasking capabilities.
  • Clear communication skills through documents and presentations.

Ways to Stand Out

  • External customer-facing experience.
  • Experience with bring-up and deployment of large clusters.
  • Systems engineering, coding, and debugging skills including C/C++, Linux kernel and drivers.
  • Hands-on experience with NVIDIA systems/SDKs (e.g., CUDA), NVIDIA Networking technologies (DPU, RoCE, InfiniBand), and/or ARM CPU solutions.
  • Familiarity with virtualization technology concepts.

Additional Information

  • Work involves approximately 20% travel for on-site customer visits and industry events.
  • Open to remote work location.
  • NVIDIA offers equity and benefits alongside base salary.