About the Role
At NVIDIA, we build firmware that helps networking products operate reliably in complex computing systems. We're hiring a Senior Firmware Engineering Manager to lead managers and teams across PCI Express firmware delivery, tools, and validation infrastructure. Our AI-native culture integrates agents, reusable skills, and continuous learning throughout the development lifecycle, from requirements and design to implementation, validation, and release. Join us to improve how firmware is built, tested, and supported!
Responsibilities
•Lead and manage firmware teams across development, releases, and customer support, including hiring, coaching, and workload planning
•Partner cross-functionally with silicon design, architecture, validation, and customer engineering to resolve issues and improve product reliability
•Drive shared tooling, lab infrastructure, and automated testing while balancing product commitments with infrastructure investments
•Build AI-native workflows and human-on-the-loop (HOTL) processes with defined autonomy boundaries, quality gates, and intervention points
•Turn engineering feedback into improved agent skills and repeatable process enhancements
What We Need to See
•Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or equivalent experience
•At least 12 overall years in engineering, including at least 6 years in engineering management
•Leadership of engineering managers or team leads, including hiring, coaching, and career development
•Embedded firmware development and debugging skills, including hardware interactions, PCI Express protocols, and silicon bringup or product integration
•Delivery of engineering tools, automated validation, or continuous integration infrastructure
•Clear technical communication and practical planning across concurrent projects
•Hands-on experience building and optimizing reusable AI agent skills through evaluation, feedback, and iteration
•An AI-native development lifecycle mindset, backed by experience building HOTL processes with human oversight, exception handling, and clear engineering accountability
Requirements
•Firmware delivery for network adapters or switches, including link training and recovery
•Reusable regression, lab automation, or debugging tools
•Scaling agent workflows across engineering teams with measurable improvements in quality, delivery time, or review effort
