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Senior Software Engineer
·Israel
Not specifiedFull-timeFrontend DevelopmentComputer Hardware Manufacturing
Seeking a Senior Software Engineer to design, implement, and upstream new capabilities for Kubernetes and CNCF projects, enabling next-generation AI infrastructure. Collaborate with engineering teams and open-source communities to solve complex distributed systems challenges.
Responsibilities
- Design, implement, and upstream new capabilities for Kubernetes and CNCF projects.
- Collaborate with engineering teams to identify AI infrastructure challenges and solve them through upstream innovation.
- Work closely with Kubernetes SIGs, Working Groups, and the broader open-source community to design and implement new capabilities.
- Participate in architecture discussions, API design, technical proposals, and code reviews.
- Build reliable, scalable infrastructure software for next-generation AI workloads.
- Write clear technical documentation and design proposals.
Requirements
- B.Sc/M.Sc or higher in Computer Science, Computer Engineering, or a related field, or equivalent practical experience.
- 5+ years of software engineering experience building distributed systems, cloud infrastructure, or platform software.
- Deep understanding of Kubernetes and the cloud-native ecosystem.
- Experience extending, building, or contributing to Kubernetes-based solutions.
- Strong communication skills and ability to collaborate across engineering teams and open-source communities.
- Curiosity, adaptability, and interest in learning AI infrastructure.
Nice to have
- Active contributor to Kubernetes, CNCF, or other open-source infrastructure projects.
- Leadership experience in open-source communities, such as maintainer, reviewer, approver, SIG/WG leadership, or similar roles.
- Experience designing Kubernetes APIs, authoring KEPs, or driving community proposals through upstream processes.
- Experience with Kubernetes scheduling, networking, Gateway API, workload APIs, or other core Kubernetes subsystems.
- Understanding of AI infrastructure, including inference systems, GPU scheduling, distributed serving, or LLM infrastructure.