Nvidia Software Engineering Manager Enterprise Platform 

United States, California 

422305682

What you'll be doing:

• Lead and manage a team of dedicated software infrastructure engineers, guiding their professional growth and project execution.

• Drive the strategic vision and roadmap for a standardized, Kubernetes-based enterprise platform across cloud and on-premise environments.

• Coordinate the development of a platform that ensures consistency, quality, and security for application and AI workload deployments.

• Define and enforce standards for infrastructure and application deployment, eliminating manual, ad-hoc processes.

• Collaborate with security teams to ensure the platform’s design and implementation are robust and secure, with a focus on authentication, authorization, and data protection.

• Work with cross-functional teams to integrate the platform into CI/CD pipelines, enabling seamless and efficient application delivery.

• Build foundational infrastructure supporting enterprise and AI applications lifecycle for NVIDIA AI Factory initiative.

What we need to see:

• BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience).

• 8+ overall years of software engineering experience with a focus on distributed systems, cloud infrastructure, or large-scale platform development.

• 3+ years of experience leading and managing a high-performing engineering team.

• Proven expertise with container orchestration technologies like Kubernetes and experience with multi-cloud or hybrid-cloud environments.

• Strong understanding of GitOps principles and experience building Git-based configuration management systems.

• Familiarity with security standard methodologies for cloud-native applications and microservices architecture.

• Excellent communication, leadership, and problem-solving skills with the ability to operate in a fast-paced, collaborative environment.

Ways to stand out from the crowd:

• Experience building platforms that support the full lifecycle of AI apps

• Open-source contributions to projects in the Kubernetes, GitOps or equivalent experience, or cloud infrastructure space.

• Deep understanding of security evaluation, threat modeling, and implementation of security controls within a platform.

• Experience in a large-scale, high-growth technology company.