Senior Field Applications Engineer – AI Infrastructure Build

NVIDIA

. Deliver direct field assistance for AI Factory build implementation, including First Time Deployments, deployment bring-up, validation, and issue triage with OEM and deployment partners .

Posted 10/14/2026full-timeHouston • Texas • United StatesSenior💰 $132,000 - $253,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data center deployment and troubleshooting, with a strong focus on infrastructure issues involving servers, GPUs, and networking. Proven ability to lead field operations, communicate effectively with cross-functional teams, and implement structured diagnostic and testing methodologies.

Highest-signal resume keywords

Data Center DeploymentField TroubleshootingInfrastructure Bring-UpLinux ProficiencyNVIDIA GPU Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Technical Field SupportRack IntegrationLarge-Scale Systems TroubleshootingDebuggingData CollectionDiagnostic Flow CraftingTest Procedure DevelopmentRoot Cause AnalysisAutomationScripting

Soft Skills

Strong Communication SkillsLeadershipCollaboration

Tools & Technologies

NVIDIA NetworkingInfiniBandRoCEHigh-Speed EthernetDeployment Tooling

Industry Keywords

AI FactoryAccelerated ComputingRack-Scale AI InfrastructureHPC DeploymentsBone-Pile Analysis

Tech Stack

Tools & technologies

Linux

About the role

Key responsibilities & impact

Deliver direct field assistance for AI Factory build implementation, including First Time Deployments, deployment bring-up, validation, and issue triage with OEM and deployment partners
Serve as a senior technical resource for urgent field issues across rack, server, GPU, networking, storage, firmware/BMC, Linux, cabling, power, thermal, and deployment-tooling domains
Deploy to partner or field sites as needed for rapid response, critical issue closure, and execution risk reduction
Drive structured triage for deployment blockers, including failure reproduction, data collection, domain isolation, critical issue packet quality, and owner alignment
Validate diagnostic flows, improve test practices, and document repeatable troubleshooting methods
Support bone-pile review and reduction by classifying failures, identifying repeat patterns, and connecting field data to root cause and corrective actions
Capture First Time Deployment lessons learned and update guidelines, readiness criteria, and execution playbooks
Provide leadership with issue status, risks, blockers, decision needs, and recovery plans during active deployments
Collaborate with NVIDIA engineering, services, architecture, program, account, field, and partner-facing teams

Requirements

What you’ll need

Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, Systems Engineering, or a related technical field (or equivalent experience)
5+ years of experience in data center deployment, rack integration, technical field support, manufacturing support, partner services, infrastructure bring-up, or large-scale systems troubleshooting
Practical experience troubleshooting infrastructure problems involving servers, GPUs, switches, storage, firmware/BMC, Linux, cabling, optics, power, thermal, or deployment tooling
Experience working directly with partner, customer, OEM, ODM, system integrator, or deployment services teams in field or production environments
Strong field troubleshooting, rigorous debugging, clean data collection, reproduction quality, and clear handoff of critical issues
Ability to operate onsite in fast-paced deployment environments and communicate with engineering, field teams, partner teams, and leadership
Strong written and verbal communication skills, including executive-ready technical issue and risk updates
Travel required up to 50%
Preferred: experience with AI Factory, accelerated computing, rack-scale AI infrastructure, large-scale GPU systems, or HPC deployments
Preferred: background with NVIDIA GPUs, NVIDIA networking, InfiniBand, RoCE, high-speed Ethernet, or large-scale cluster bring-up
Preferred: experience crafting diagnostic flows, test procedures, readiness playbooks, blocking issue templates, or best-practice libraries
Preferred: experience with bone-pile analysis, RMA/failure pattern review, root cause feedback loops, or systemic quality improvement
Preferred: strong Linux, scripting, automation, telemetry, or log-analysis skills

Benefits

Comp & perks

Equity
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