Sr. Software Engineer, Compute Infrastructure; Mountain View

Location

Mountain View, CA.

• Contribute directly to Linked In’s Compute infrastructure strategy.
• Build and operate a platform that allocates hardware resources with necessary physical and logical distribution for fault tolerance and easy maintenance.
• Build and operate world-class high performance scheduling and deployment solutions, including managing large Kubernetes clusters to place stateless and stateful services, ML workloads, and short-running jobs efficiently.
• Help up-level and coach a large team of talented developers.

• 5 years of industry experience in software design, development, and algorithm-related solutions.
• 5 years of experience programming in object-oriented languages such as Java, Go, C/C++, Rust, or Python.
• Hands‑on experience developing large‑scale distributed systems.
• 2 years of experience as an architect or in a technical leadership position.
• BS/BA in Computer Science or a related technical field, or equivalent technical experience.

• 10 years of experience in software design, development, and algorithm-related solutions with at least 5 years in a technical leadership position.
• 10 years of programming experience in an object-oriented language such as Go, Java, C/C++, or Rust.
• 5 years of experience building large-scale compute infrastructure and distributed systems.
• Demonstrated understanding of operating system fundamentals, container technologies, and systems knowledge.
• Experience leading technical teams and mentoring other engineers.
• Experience building and operating cluster management solutions such as Kubernetes.
• Experience with IaaS systems and capacity management.
• Experience with networking and security principles.
• Deep understanding of Kubernetes architecture and key components (API server, scheduler, kubelet, etc.), with a proven track record of deploying, managing, and troubleshooting Kubernetes clusters.
• Strong proficiency in Golang, the primary language for this role.
• Solid understanding of networking concepts relevant to Kubernetes, including CNI plugins and pod networking.
• Knowledge of Kubernetes security best practices such as RBAC, network policies, and Pod security policies.
• Proficiency with monitoring and logging tools such as Prometheus, Grafana, and Fluentd.

Pay range: $198,000 to $326,000. The total compensation may also include an annual performance bonus, stock options, benefits, and other incentive compensation plans. For more information, visit

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