Senior AI Infrastructure Engineer - EDA Infrastructure
$184k - $357k • Remote • US, CA, Remote
Posted 5d ago
Job Location
US, CA, Remote
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Infrastructure Engineer
About the job
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.
Responsibilities
- 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 for consistent telemetry generation and consumption.
- Deliver dashboards, alerting, and analysis capabilities to improve service visibility, detection, and troubleshooting.
- Standardize and automate incident, maintenance, service on-call, and support on-call workflows.
- Integrate operational data and lifecycle signals to improve ownership, escalation, communication, and post-incident learning.
- Build reporting and AI-assisted tooling to reduce manual toil and improve operational responsiveness.
- 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 connecting clusters, hardware, services, teams, and operational workflows.
- Provide self-service discovery capabilities for engineers to quickly identify what they operate, who owns it, and how to support it.
Requirements
- 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 spanning internal teams and external partners across engineering, product, finance, and security.
Benefits
- Equity
- Benefits