NVIDIA is looking to build and maintain a Kubernetes-based platform that standardizes and automates the building, deployment, and management of enterprise and AI applications as part of the NVIDIA AI Factory initiative. The goal is to ensure consistency, security, and efficiency at scale across both cloud and on-premise environments.
Requirements
- 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.
- Experience building platforms that support the full lifecycle of AI apps
- Deep understanding of security evaluation, threat modeling, and implementation of security controls within a platform.
Responsibilities
- 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.
Other
- BS, MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience).
- Excellent communication, leadership, and problem-solving skills with the ability to operate in a fast-paced, collaborative environment.
- Open-source contributions to projects in the Kubernetes, GitOps or equivalent experience, or cloud infrastructure space.
- Experience in a large-scale, high-growth technology company.
- NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer.
