Senior AI Infra Engineer – EDA Platforms & Telemetry

Nvidia Corporation in; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA seeks a Senior AI Infrastructure Engineer for EDA Infrastructure (Finance) in Santa Clara to design and run telemetry, data catalogs, and automation across on‑prem and cloud environments. You will partner with product, finance, and security teams to build scalable systems and observability tooling.

The role emphasizes cross‑functional leadership, production-grade infrastructure, and a strong focus on reliability and security within automotive-grade AI workflows.

Qualifications

• BS degree in Computer Science, Computer Engineering, or a related technical field, or equivalent experience.
• 8+ years of experience in infrastructure security, platform engineering, or security tooling.
• Proficiency in Python, Go, Typescript, or Java.
• Strong understanding of software and infrastructure principles, with production experience.
• Ability to lead cross-functional initiatives across engineering, product, finance, and security.

Responsibilities

• Build and operate scalable telemetry pipelines for metrics, logs, traces, and events across on-premise, CSP, and NCP clusters.
• Standardize and automate incident, maintenance, service on-call, and support on-call workflows across HWInf.
• Create consistent data models and integration pipelines that connect clusters, hardware, services, teams, and operational workflows.

Skills

Python

Go

Typescript

Java

Education

BS degree in Computer Science or related field

Job description

NVIDIA seeks a Senior AI Infrastructure Engineer for EDA Infrastructure (Finance) in Santa Clara to design and run telemetry, data catalogs, and automation across on‑prem and cloud environments. You will partner with product, finance, and security teams to build scalable systems and observability tooling.

The role emphasizes cross‑functional leadership, production-grade infrastructure, and a strong focus on reliability and security within automotive-grade AI workflows.