This role pays more than
75%
of similar roles. Most pay
$185,000–$273,149
— the shaded band above.
At the midpoint, this role pays about
$271k
versus about
$229k
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
1371 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1096 roles with salary data.
Engineering Manager – AI Platform & SRE
As an Engineering Manager within the Site Reliability Engineering team, you will lead a group of engineers responsible for building and operating resilient AI platform capabilities at enterprise scale. You will define technical strategies and roadmaps to deliver highly available, scalable distributed systems that support enterprise AI agent products. Your daily work involves driving the development of AI agents and intelligent automation for incident response, troubleshooting, and remediation while improving developer experience through infrastructure-as-code and self-service platforms. The role requires expertise in Linux, networking, Kubernetes, and public cloud platforms like AWS, Azure, or GCP. You will utilize languages such as Python, Go, TypeScript, JavaScript, or Java to manage production services. Key technical focuses include observability via OpenTelemetry, capacity management, and establishing service-level objectives to ensure reliable infrastructure for complex AI operations.
What does a Engineering Manager earn in California?
Median $290250 from 62 postings across 17 companies.
Lead and develop a team of SRE, platform, and software engineers for the AI Platform Runtime.
Define technical strategies, priorities, and roadmaps aligned with product and business objectives.
Oversee the design and delivery of highly available, scalable, and secure distributed systems for enterprise AI products.
Drive the development of AI agents and intelligent automation for incident response and platform operations.
Establish measurable reliability goals using SLIs, SLOs, error budgets, and capacity models.
Improve developer experience through self-service platforms, infrastructure-as-code, and standardized delivery patterns.
Manage critical incidents and conduct blameless postmortems to implement durable corrective actions.
Recruit, coach, and mentor engineers to foster a high-performing and inclusive team environment.
What we're looking for
10+ years of experience in Site Reliability Engineering, Platform Engineering, Software Engineering, Cloud Infrastructure, or a related technical field.
3+ years managing or formally leading engineering teams responsible for complex production systems.
Technical foundation in distributed systems, Linux, networking, Kubernetes, and public cloud platforms like AWS, Azure, or GCP.
Experience leading teams building production software and automation using Python, Go, TypeScript, JavaScript, or Java.
Solid understanding of observability at scale, including OpenTelemetry, metrics, logs, distributed tracing, profiling, and operational analytics.
Experience applying SRE practices such as SLOs, error budgets, capacity management, incident management, and blameless postmortems.
Demonstrated ability to create technical roadmaps, manage competing priorities, and deliver measurable outcomes across multiple teams.
Hands-on experience with AI agents, agentic workflows, or intelligent automation for infrastructure (preferred); experience scaling SRE functions in large enterprises (preferred).
Deep Learning
Machine Learning
LLMs
Computer Vision
CUDA
C++
C
OpenMP
MPI
pthreads
GPU Architecture
Parallel Programming
Linear Algebra
Performance Optimization
Multimodal Architectures