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 a unique opportunity to work on high-impact projects that will influence LinkedIn's entire engineering organization.

The position focuses on the LinkedIn Kubernetes Infrastructure team, which provides an on-premises Kubernetes platform serving the entire company. You'll be responsible for creating Kubernetes clusters on-demand, developing multi-cluster solutions, automating upgrades, and implementing intelligent health detection and remediation systems.

As a Staff Engineer, you'll play a crucial role in designing and implementing solutions that enable LinkedIn to scale its Compute Infrastructure to meet the demands of its growing user base. You'll work alongside experienced engineers to develop robust, scalable, and efficient solutions while collaborating with cross-functional teams in a fast-paced environment.

Key responsibilities include owning technical strategy for complex requirements, designing and optimizing large-scale distributed systems, improving system observability, mentoring other engineers, and driving innovation. You'll need expertise in Kubernetes, distributed systems, and preferably Golang.

The role offers the flexibility of hybrid work, allowing you to work both remotely and from LinkedIn offices in Mountain View, San Francisco, or Bellevue. You'll be part of a company culture that values well-being, innovation, and professional growth. LinkedIn offers competitive compensation and benefits, demonstrating their commitment to attracting and retaining top talent.

This is an excellent opportunity for experienced engineers who want to work on cutting-edge infrastructure technology at scale, while contributing to LinkedIn's mission of creating economic opportunity for every member of the global workforce. The role combines technical leadership, hands-on development, and the chance to shape the future of LinkedIn's infrastructure.