← All roles

Senior Solutions Architect, AI and HPC Infrastructure

NVIDIA· Architect, Solutions
Apply on company site
Hybrid (US: TX (Remote))$184k - $287.5kfull-timePosted 4d ago

About the role

AI Solutions Architect focused on helping energy-sector customers design, deploy, and optimize NVIDIA accelerated infrastructure for AI/ML workloads across data centers and edge environments, including training, inference, and agentic AI/HPC workloads.

Responsibilities

  • Partner with energy-sector customers, ISVs, and account teams on discovery, architecture reviews, technical deep dives, POCs, benchmarks, demos, and production deployment guidance for AI infrastructure.
  • Advise on the design, build-out, and optimization of accelerated AI infrastructure for energy customers, including large-scale GPU clusters, AI factories, and edge deployments.
  • Support infrastructure design across compute, networking, storage, containers, observability, security, power, and data center operations for energy-sector AI workloads.
  • Drive adoption of systems monitoring, telemetry, and management tools to improve cluster utilization, reliability, performance, and workload insight.
  • Document what you learn and teach others — through targeted samples, whitepapers, blogs, and working through hard problems with customers.
  • Build repeatable reference architectures, deployment guides, sizing guidance, benchmark reports, technical playbooks, demos, and whitepapers for energy-sector AI infrastructure.
  • Strategically partner with flagship customers and industry-specific solution partners targeting our computing platform.
  • Collaborate primarily through virtual tools, and be empowered to find the best way to make our partners and customers successful.
  • Travel up to 20% for customer meetings may be required.

Qualifications

  • BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, other Engineering, or related field (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, with 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, and understanding of data center networking technologies such as InfiniBand, Ethernet, RDMA, network configuration, and performance tuning.
  • Familiarity with infrastructure requirements for AI workloads, including distributed training, inference serving, model deployment, storage performance, and cluster reliability.
  • Working knowledge of one or more energy sectors (power generation, oil & gas, transmission and distribution / grid, or renewables) and their operational and IT environments.
  • Excellent presentation, communication, problem-solving, documentation, and collaboration skills.
  • Strong problem structuring and the self-direction to drive ambiguous, multi-stakeholder projects to results.

Skills

Required:AI infrastructure design and deployment

Benefits

  • equity
  • benefits (see NVIDIA benefits)
Last updated Oct 23, 2026. Interested? Apply on the company site.

About NVIDIA

World Leader in AI Computing

NVIDIA invents the GPU and drives advances in AI, HPC, gaming, creative design, autonomous vehicles, and robotics.

AIautonomous vehiclesgaminggpugraphics cardhigh performance computingliquid-ai-recruiting-targetllm
Company profileWebsite

More open roles at NVIDIA