Staff Software Engineer - Compute Infrastructure

LinkedIn is the worlds largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. Were also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture thats built on trust, care, inclusion, and fun where everyone can succeed. Join us to transform the way the world works. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. LinkedIn operates one of the largest privately managed compute infrastructures in the world outside the public cloud providers. As a Staff Software Engineer on the Compute Infrastructure team, you will help build and evolve the platform that powers LinkedIn at every layer — the real-time services behind products serving over a billion members, large-scale data and analytics pipelines processing petabytes daily, and the AI/ML infrastructure driving recommendations, search relevance, and generative AI at scale. The Compute Infrastructure stack is LinkedIn's internal private cloud, purpose-built to meet the company's unique scaling challenges. The platform is deeply Kubernetes-centric and continuously evolving to stay at the forefront of industry trends. You will work on problems that span large-scale workload orchestration, multi-cluster operations, platform reliability and efficiency, GPU compute optimization for AI/ML, and fleet health at scale — all at a scale that few organizations in the world encounter. In this role, you will design and implement solutions that enable LinkedIn to scale its compute infrastructure to meet the demands of a rapidly growing user base and an ever-expanding product portfolio. You will work closely with a team of talented engineers to develop and operate systems that are robust, scalable, and efficient. You will also collaborate with cross-functional teams and thrive in a fast-paced, dynamic environment. Responsibilities Enable thousands of LinkedIn engineering teams to deploy and operate reliably — driving impact across areas such as CI/CD pipelines that deliver a seamless developer experience, a workload platform that provides resilient orchestration at scale, a self-healing host management system with intelligent health detection and automated remediation, Kubernetes cluster lifecycle and infrastructure, and GPU compute infrastructure powering AI/ML workloads, all underpinned by intelligent autoscaling, resource allocation, and capacity management Accelerate LinkedIn's product velocity by improving platform observability, deployment safety, and release throughput Shape technical direction across team boundaries, ensuring the platform evolves ahead of demand from new products, AI workloads, and growth Strengthen the team by mentoring engineers, raising the technical bar, and fostering a culture of engineering excellence Resolve deep production issues that cut across Kubernetes internals, operating system behavior, and distributed system interactions Basic Qualifications BA/BS Degree in Computer Science or related technical discipline, or equivalent practical experience 4+ years of industry experience in software design, development, and algorithm-related solutions 4+ years of experience programming in languages such as Go or Python Hands-on experience developing distributed systems, large-scale platforms, or backend services Experience with Kubernetes or similar container orchestration platforms Preferred Qualifications BS and 8+ years of relevant work experience, MS and 7+ years of relevant work experience, or PhD and 4+ years of relevant work experience Experience architecting, building, and operating large-scale distributed systems Experience with Kubernetes controller development and cluster lifecycle automation Experience contributing to or maintaining open-source projects Demonstrated ability to leverage agentic development tools and workflows to accelerate engineering productivity Suggested Skills Distributed Systems Golang Kubernetes Technical Leadership You will Benefit from our Culture We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels. LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $175,000 - $287,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits . Equal Opportunity Statement We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class. LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful. If you need a Reasonable Accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us and describe the specific Accommodation requested for a disability-related limitation. 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