below marketmost similar roles pay hereabove market
This role pays more than
85%
of similar roles. Most pay
$144,350–$231,950
— the blue band above.
At the midpoint, this role pays about
$236k
versus about
$188k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1623 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1110 roles with salary data.
The Senior AI Infrastructure Engineer - EDA Infrastructure joins the AI Infrastructure team to build systems, tooling, and data infrastructure for GPU cloud services. This role involves building and operating scalable telemetry pipelines for metrics, logs, traces, and events across on-premise, CSP, and NCP clusters. You will establish common instrumentation patterns, deliver dashboards and alerting capabilities, and automate incident management workflows. Key responsibilities include maintaining physical hardware and software catalogs as trusted sources of truth and creating consistent data models for infrastructure inventory. The role requires proficiency in Python, Go, Typescript, or Java, alongside experience in infrastructure platform engineering. You will solve technical problems related to service visibility, operational excellence, and self-service discovery for critical AI platforms while managing complex dependencies across engineering, product, finance, and security.
Build and operate scalable telemetry pipelines for metrics, logs, traces, and events across various clusters.
Establish common instrumentation, collection, storage, and access patterns for consistent telemetry consumption.
Deliver dashboards, alerting, and analysis capabilities to improve service visibility and troubleshooting.
Standardize and automate incident, maintenance, and on-call workflows across hardware infrastructure.
Build reporting and AI-assisted tooling to reduce manual toil and improve operational responsiveness.
Maintain physical hardware and software catalogs as trusted sources of truth for infrastructure inventory.
Create data models and integration pipelines connecting clusters, hardware, services, and operational workflows.
Provide self-service discovery capabilities for engineers to identify ownership and support procedures.
What we're looking for
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 across engineering, product, finance, and security.
Experience building and operating incident-management processes with internally built and/or externally vended SaaS tools (preferred).
Experience building, deploying, and maintaining ML models in production systems with familiarity with AI agent frameworks or orchestration tools (preferred).
Experience building and operating modern observability platforms to deliver scalable metrics, logs, traces, and profiling (preferred).
Python
C/C++
Large Language Models
AI Agents
Retrieval-Augmented Generation
CUDA
MLOps
GPU Computing
Data Pipelines
APIs
system-design
Production Software
Model Evaluation
AI Observability
Workflow Orchestration
Silicon Bring-up
OCI
Python
Java
C
C++
GoLang
Shell Scripting
Linux
SQL
MySQL
Redis
Memcache
RoCE
Infiniband
Infrastructure as Code
Distributed Systems
System Design
Fault Tolerance
Telemetry Systems