Job description

AI Infrastructure Engineers at NVIDIA build the systems, tooling, and data infrastructure that enable operation of our GPU cloud services. We are enabling engineering teams to innovate while proactively identifying, tracking, and mitigating risks across the entire technical task. This role is ideal for engineers who thrive at the intersection of product, infrastructure, and software engineering and who want to build automated, intelligence-driven systems that protect NVIDIA’s most critical AI platforms. What you’ll be doing: Telemetry • Build and operate scalable telemetry pipelines for metrics, logs, traces, and events across on-premise, CSP, and NCP clusters. • Establish common instrumentation, collection, storage, and access patterns so teams can generate and consume telemetry consistently. • Deliver dashboards, alerting, and analysis capabilities that improve service visibility, detection, and troubleshooting. Operational Excellence • Standardize and automate incident, maintenance, service on-call, and support on-call workflows across HWInf. • Integrate operational data and lifecycle signals to improve ownership, escalation, communication, and post-incident learning. • Build reporting and AI-assisted tooling that reduces manual toil and improves operational responsiveness. Cataloging and Inventory • Build and maintain physical hardware and software catalogs as trusted sources of truth for infrastructure inventory, service ownership, dependencies, and documentation. • Create consistent data models and integration pipelines that connect clusters, hardware, services, teams, and operational workflows. • Provide self-service discovery capabilities so engineers can quickly identify what they operate, who owns it, and how to support it. What we need to see: • BS degree in Computer Science, Computer Engineering, or a related technical field, or equivalent experience. • 8+ years of experience in infrastructure platform engineering, or tooling. • Proficiency in one or more programming languages such as Python, Go, Typescript, or Java. • Strong understanding of software and infrastructure principles, with experience applying them in production environments. • Ability to lead cross-functional initiatives that span internal teams and external partners in varying disciplines across engineering, product, finance, and security. Ways to stand out from the crowd: • Experience building and operating incident-management processes with internally built and/or externally vended SaaS tools • Experience working with building, deploying, and maintaining ML models in production systems along with familiarity with AI agent frameworks or orchestration tools • Experience building and operating modern observability platforms to deliver scalable metrics, logs, traces, and profiling Experience working with service catalog and configuration management databases (CMDB) NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you. NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. If you're creative and self-motivated, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. 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. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 2, 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

Build and operate scalable telemetry pipelines for metrics, logs, traces, and events across on-premise, CSP, and NCP clusters.
Establish common instrumentation, collection, storage, and access patterns so teams can generate and consume telemetry consistently.
Deliver dashboards, alerting, and analysis capabilities that improve service visibility, detection, and troubleshooting.
Operational Excellence
Standardize and automate incident, maintenance, service on-call, and support on-call workflows across HWInf.
Integrate operational data and lifecycle signals to improve ownership, escalation, communication, and post-incident learning.
Build reporting and AI-assisted tooling that reduces manual toil and improves operational responsiveness.
Cataloging and Inventory
Build and maintain physical hardware and software catalogs as trusted sources of truth for infrastructure inventory, service ownership, dependencies, and documentation.
Create consistent data models and integration pipelines that connect clusters, hardware, services, teams, and operational workflows.
Provide self-service discovery capabilities so engineers can quickly identify what they operate, who owns it, and how to support it.
BS degree in Computer Science, Computer Engineering, or a related technical field, or equivalent experience.
8+ years of experience in infrastructure platform engineering, or tooling.
Proficiency in one or more programming languages such as Python, Go, Typescript, or Java.
Strong understanding of software and infrastructure principles, with experience applying them in production environments.
Ability to lead cross-functional initiatives that span internal teams and external partners in varying disciplines across engineering, product, finance, and security.
Experience building and operating incident-management processes with internally built and/or externally vended SaaS tools
Experience working with building, deploying, and maintaining ML models in production systems along with familiarity with AI agent frameworks or orchestration tools
Experience building and operating modern observability platforms to deliver scalable metrics, logs, traces, and profiling Experience working with service catalog and configuration management databases (CMDB)
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until October 2, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

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

Keywords to mirror

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