Nvidia
Senior Solutions Architect, AI and HPC Infrastructure
US, TX, Remote · Senior
Sponsorship not specifiedDetected 1 day ago
Node.jsDistributed SystemsCloud PlatformsDockerCI/CDMachine LearningLLMsRAGAgentic AIBusiness DevelopmentCommunicationCollaborationProblem Solving
Stay score
odds of building a lasting career here
42Risky
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
Thin sponsorship signal and lottery-bound. A low-probability bet with your clock running. Prioritize cap-exempt roles and proven entry-level sponsors first.
Lottery odds assume a STEM candidate.
Personalize to your clock →Employer immigration record
from this employer's Department of Labor filings
Green-card filing pattern in this occupation
Context, not a finding about this posting: of this employer's 399 green-card filings in this occupation, 96% were for a worker who already held the job.
Green-card follow-through: 95%
Of 584 labor certifications old enough to have been used, 29 expired without the employer filing the next step. Median time from filing to decision: 497 days.97% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.
Files H-1B transfers
620 transfer filings in the last year, covering 1241 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.
Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.
Community outcomes
No reports yet — be the first to help the next applicant.
About the role
- This role will focus on helping energy accounts from datacenter to the edge adopt NVIDIA accelerated infrastructure for training, fine-tuning, inference, retrieval, and agentic AI and HPC workloads.
- This is an excellent opportunity to work in an interdisciplinary team at NVIDIA!
- What we need to see: BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, other Engineering, or related field (or equivalent experience).
Responsibilities
- 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.
- Build repeatable reference architectures, deployment guides, sizing guidance, benchmark reports, technical playbooks, demos, and whitepapers for energy-sector AI infrastructure.
- Strong problem structuring and the self-direction to drive ambiguous, multi-stakeholder projects to results.
- Engaging with internal developers, researchers, data scientists, and senior leaders is a core part of the role and offers exposure to a wide range of partners and challenges.
- 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.
- Document what you learn and teach others - through targeted samples, whitepapers, blogs, and working through hard problems with customers.
- 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.
Requirements
- Travel up to 20% for customer meetings may be required.
Compensation
- Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.
- The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
Company info
- Ways to stand out from the crowd: Experience architecting AI factories, large GPU clusters, multi-node training environments, or production inference platforms.
This listing is sourced directly from Nvidia's careers page and normalized into a canonical job model.