Senior AI Infrastructure Engineer - EDA Infrastructure

Details

AI Infrastructure Engineers at NVIDIA build the systems, tooling, and data infrastructure that enable operation of NVIDIA's GPU cloud services. This role operates at the intersection of product, infrastructure, and software engineering to build automated, intelligence-driven systems that protect critical AI platforms.

Responsibilities

Telemetry

• Build and operate scalable telemetry pipelines for metrics, logs, traces, and events across on-premises, 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.

Requirements

• Bachelor's 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 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 spanning internal teams and external partners across engineering, product, finance, and security.

Preferred Qualifications

• Experience building and operating incident-management processes with internally built or externally provided SaaS tools.
• Experience building, deploying, and maintaining machine learning models in production systems, along with familiarity with AI agent frameworks or orchestration tools.
• Experience building and operating modern observability platforms for scalable metrics, logs, traces, and profiling.
• Experience working with service catalogs and configuration management databases (CMDBs).

Compensation and Benefits

• Base salary range for Level 4: $184,000–$287,500 USD per year.
• Base salary range for Level 5: $224,000–$356,500 USD per year.
• Eligibility for equity and benefits.
• NVIDIA uses AI tools in its recruiting processes.
• Applications will be accepted at least until September 4, 2026.
• This posting is for an existing vacancy.
• NVIDIA is an equal opportunity employer committed to fostering an inclusive work environment.