Job description

NVIDIA is looking for a Senior Field Applications Engineer to assist with AI Factory build implementation and swift assistance alongside OEM and deployment collaborators. This position offers practical, on-site technical support for initial deployments, critical field challenges, preparation shortfalls, and repeated build issues that need focused technical resolution. You will collaborate with NVIDIA engineering, services, architecture, program, account, field, and partner-facing teams to identify issues, shorten resolution times, validate diagnostic flows, and transform field findings into repeatable guidelines. This role suits a senior technical contributor who can work onsite, provide clarity during critical issues, and help establish a more consistent approach for AI Factory build-outs. This is a field-facing role with encouraged onsite support during critical build, bring-up, validation, and blocking issue windows. What you'll be doing: • Deliver direct field assistance for AI Factory build implementation, encompassing 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 involving customer concerns across rack, server, GPU, networking, storage, firmware/BMC, Linux, cabling, power, thermal, and deployment-tooling domains. • Deploy to partner or field sites as needed to support targeted rapid response, critical issue closure, and execution risk reduction. • Drive structured triage for deployment blockers, including failure reproduction, data collection, domain isolation, quality of critical issue packets, and owner alignment. • Help reduce time to resolution by validating diagnostic flows, improving test practices, and detailing repeatable troubleshooting methods. • Support bone-pile review and reduction by helping classify failures, identify repeat patterns, and connect field data to root cause and corrective actions. • Capture First Time Deployment lessons learned and update guidelines, readiness criteria, and execution playbooks for reuse across OEM engagements. • Provide concise leadership access to issue status, risk, blockers, decision needs, and recovery plans during active deployments. What we need to see: • 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 intricate infrastructure problems related to 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 troubleshooting in the field, including rigorous debug, clean data collection, reproduction quality, and clear handoff of critical issues. • Ability to operate onsite in fast-paced deployment environments while communicating clearly with engineering, field teams, partner teams, and leadership. • Strong written and verbal communication skills, including the ability to summarize complex technical issues into executive-ready status and risk updates. • Travel required (up to 50%) to support field engagements, partner sites, and deployment activities. Ways to stand out from the crowd: • Experience with AI Factory, accelerated computing, rack-scale AI infrastructure, large-scale GPU systems, or HPC deployments. • Background with NVIDIA GPUs, NVIDIA networking, InfiniBand, RoCE, high-speed Ethernet, or large-scale cluster bring-up. • Experience crafting or improving diagnostic flows, test procedures, readiness playbooks, blocking issue templates, or best-practice libraries. • Experience with bone-pile analysis, RMA/failure pattern review, root cause feedback loops, or systemic quality improvement. • Strong Linux, scripting, automation, telemetry, or log-analysis skills. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 132,000 USD - 207,000 USD for Level 3, and 160,000 USD - 253,000 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 18, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

Must-haves

Deliver direct field assistance for AI Factory build implementation, encompassing 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 involving customer concerns across rack, server, GPU, networking, storage, firmware/BMC, Linux, cabling, power, thermal, and deployment-tooling domains.
Deploy to partner or field sites as needed to support targeted rapid response, critical issue closure, and execution risk reduction.
Drive structured triage for deployment blockers, including failure reproduction, data collection, domain isolation, quality of critical issue packets, and owner alignment.
Help reduce time to resolution by validating diagnostic flows, improving test practices, and detailing repeatable troubleshooting methods.
Support bone-pile review and reduction by helping classify failures, identify repeat patterns, and connect field data to root cause and corrective actions.
Capture First Time Deployment lessons learned and update guidelines, readiness criteria, and execution playbooks for reuse across OEM engagements.
Provide concise leadership access to issue status, risk, blockers, decision needs, and recovery plans during active deployments.
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 intricate infrastructure problems related to 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 troubleshooting in the field, including rigorous debug, clean data collection, reproduction quality, and clear handoff of critical issues.
Ability to operate onsite in fast-paced deployment environments while communicating clearly with engineering, field teams, partner teams, and leadership.
Strong written and verbal communication skills, including the ability to summarize complex technical issues into executive-ready status and risk updates.
Travel required (up to 50%) to support field engagements, partner sites, and deployment activities.
Experience with AI Factory, accelerated computing, rack-scale AI infrastructure, large-scale GPU systems, or HPC deployments.
Background with NVIDIA GPUs, NVIDIA networking, InfiniBand, RoCE, high-speed Ethernet, or large-scale cluster bring-up.
Experience crafting or improving diagnostic flows, test procedures, readiness playbooks, blocking issue templates, or best-practice libraries.
Experience with bone-pile analysis, RMA/failure pattern review, root cause feedback loops, or systemic quality improvement.
Strong Linux, scripting, automation, telemetry, or log-analysis skills.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until October 18, 2026.
This posting is for an existing vacancy.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiswift

Platform: eightfold
Effort: medium