Senior Solutions Architect – AI Infrastructure, Enterprise ISVs

NVIDIA

AI Solutions Architect focusing on helping ISVs adopt NVIDIA's accelerated infrastructure for AI workloads. Partnering on architecture reviews and production deployment guidance.

Posted 7/16/2026full-timeRemote • California, New York, Texas, Washington • 🇺🇸 United StatesSenior💰 $184,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and optimizing accelerated AI infrastructure, including large-scale clusters and distributed systems. Proficient in AI cluster orchestration, automation, and CI/CD deployment pipelines, with strong communication and problem-solving abilities.

Highest-signal resume keywords

AI Infrastructure DesignAccelerated ComputingDistributed SystemsCI/CD Deployment PipelinesData Center Networking

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

AI Cluster OrchestrationHigh-Performance ComputingInfrastructure OptimizationAutomationPerformance TuningModel DeploymentDistributed TrainingInference ServingTechnical DocumentationBenchmarking

Soft Skills

CommunicationProblem-SolvingCollaborationPresentationDocumentation

Tools & Technologies

Telemetry ToolsManagement ToolsNetworking TechnologiesContainersStorage Solutions

Industry Keywords

Cloud InfrastructureData Center OperationsCluster ReliabilityWorkload InsightReference Architectures

Tech Stack

Tools & technologies

CloudDistributed Systems

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

You will also be eligible for equity and benefits.