Manager, Software Engineering - Security Firmware

Responsibilities

• Own the delivery, quality, and security posture of root-of-trust firmware across NVIDIA's data center compute platforms, from architecture through production release.
• Lead, mentor, and grow a distributed team of senior firmware and security engineers, fostering a culture of autonomy, accountability, and continuous learning.
• Drive adoption of modern software engineering practices: rigorous code review, robust CI/CD pipelines, automated testing and fuzzing for security-critical code paths, and systematic threat modeling.
• Champion an AI-forward engineering culture - actively using and encouraging AI coding assistants, automated analysis tools, and LLM-assisted workflows to improve team velocity and code quality.
• Establish and maintain effective asynchronous-first communication practices that enable a geographically distributed team to collaborate with clarity and minimal friction across time zones.
• Partner with security architects, hardware engineers, system software teams, and data center customers to define requirements, review designs, and ensure the firmware stack meets NVIDIA's highest reliability and security standards.
• Own project planning and execution: manage milestones, track risks, communicate status clearly to senior leadership, and make rapid decisions when priorities conflict.
• Drive continuous improvement in engineering processes, tooling, and team structure - identifying bottlenecks and acting decisively to improve throughput and morale.
• What We Need to See:
• Demonstrated experience managing distributed, remote-first engineering teams across multiple time zones, with a clear philosophy for enabling autonomous, high-agency contributors.
• Deep familiarity with modern software engineering methodologies: agile/iterative development, continuous integration, test-driven development, and systematic code review practices.
• Genuine, demonstrable AI-forward mindset: you actively use AI coding assistants and LLM-based tooling in your own workflows and have driven adoption of these tools within engineering teams.
• Solid technical foundation in C/C++ and embedded systems, with the ability to engage credibly in deep technical discussions about firmware architecture, memory safety, and hardware-software interfaces.
• Excellent written and verbal communication skills, with a strong preference for written communication that creates clarity and institutional memory for a remote team.
• Comfortable with ambiguity and complexity; you make sound decisions quickly with incomplete information and course-correct without friction.
• Ways to Stand Out from the Crowd:

Additional Information

NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. GPU deep learning ignited the modern AI era - with NVIDIA hardware and software acting as the foundation for the world's most ambitious AI, robotics, and autonomous systems workloads. Today, we are the AI computing company. NVIDIA Data Center Systems - including DGX, HGX, and MGX platforms - deliver the world's leading infrastructure for AI at scale. We are growing our teams with the most thoughtful, creative, and driven people on the planet. We are looking for a Software Engineering Manager to lead a team building security-critical root-of-trust (RoT) firmware for NVIDIA Data Center Systems. This firmware sits at the deepest layer of platform trust - establishing hardware-rooted security for boot integrity, cryptographic attestation, and secure lifecycle management across NVIDIA's next-generation data center compute platforms. Your team is distributed across multiple time zones, with highly experienced individual contributors who operate with a significant degree of autonomy. Your role is not to micromanage - it is to set clear direction, unblock hard problems, cultivate a culture of excellence, and ensure that your engineers have what they need to do their best work. You will be expected to lead by example: staying technically sharp, embracing AI-assisted engineering workflows, and modeling the kind of clear thinking and high standards that NVIDIA is known for.

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