Staff Software Engineer - Compute Infrastructure

LinkedIn, the world's largest professional network, is seeking a Staff Software Engineer to join their Compute Infrastructure team. This role presents an exciting opportunity to work on LinkedIn's next-generation infrastructure and platforms, specifically focusing on the company-wide Kubernetes platform.

The position involves working with a team of experienced engineers to develop and operate robust, scalable solutions that will help LinkedIn scale its Compute Infrastructure to meet the demands of its rapidly growing user base. As a staff engineer, you'll be responsible for designing and implementing solutions that enable efficient cluster creation, multi-cluster solutions, automated upgrades, and intelligent health monitoring and remediation.

The role offers a hybrid work arrangement, allowing flexibility to work from home while maintaining important in-person collaboration when needed. You'll be based in one of LinkedIn's major tech hubs - Mountain View, San Francisco, or Bellevue - and will be part of a team that values innovation, mentorship, and technical excellence.

Key responsibilities include owning technical strategy for complex requirements, designing and optimizing large-scale distributed systems, improving system observability, and mentoring other engineers. You'll work with cutting-edge technologies like Kubernetes, Go, and various distributed systems tools while helping shape the technical culture of a growing team.

The ideal candidate brings significant experience in distributed systems, Kubernetes ecosystem, and backend development. You'll have the opportunity to make a substantial impact on LinkedIn's infrastructure while working in an environment that promotes learning, collaboration, and career growth.

This role offers competitive compensation and benefits, reflecting LinkedIn's commitment to attracting and retaining top talent. Join a company that's focused on creating economic opportunity for every member of the global workforce while working on challenging technical problems at scale.