Fellow, Software Engineering- Infrastructure at LinkedIn3

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 is seeking a Fellow to provide the highest level of technical leadership for the Infrastructure organization. Fellows at LinkedIn represent the pinnacle of the individual contributor track — deeply technical visionaries who define the future of their discipline, shape the direction of the company, and drive innovation that influences the broader industry. As a Fellow in Infrastructure, you will set the long-term technical agenda across the full stack of systems that power LinkedIn — from physical and compute foundations through distributed services, data platforms, online applications, and AI infrastructure — serving over one billion members globally. You will be one of the most senior technical voices in an organization spanning all layers of the Infra stack (Physical Infra, Core Infra, Data Infra, Online Infra, AI Infra, and Reliability Infra), and will have company-wide influence on how LinkedIn builds, operates, and evolves its infrastructure for the next decade. In this role, you will lead advancements in distributed systems, AI-first development, and developer productivity, while serving as the technical authority for LinkedIn’s private cloud infrastructure — driving efficiency, agility, and cost attribution at company scale.   Responsibilities • Define and champion the long-term technical vision and strategy for LinkedIn’s Infrastructure organization as a whole, influencing the direction of LinkedIn’s entire engineering platform • Identify and solve the most complex and consequential technical challenges across the infrastructure stack — spanning compute, storage, networking, data pipelines, online serving, and AI infrastructure — at LinkedIn scale, setting a new bar for what is possible • Drive company-wide architectural decisions spanning service delivery, distributed databases, caching, data processing, AI training and serving infrastructure, and reliability systems, ensuring alignment with LinkedIn’s multi-year technology roadmap • Establish the technical standards, design principles, and engineering culture that guide the Infrastructure organization and elevate engineering practices across LinkedIn broadly • Drive advancements in developer productivity — shaping the tools, frameworks, and engineering practices that enable LinkedIn’s thousands of engineers to build, iterate, and ship software faster and more reliably • Lead infrastructure initiatives to increase efficiency, fungibility, and agility at hyperscale • Lead LinkedIn’s infrastructure transformation toward AI-native paradigms — evaluating and adopting transformative technologies that position LinkedIn’s Infrastructure as an industry leader in building and operating AI-first infrastructure at scale • Collaborate with Distinguished Engineers, Principal Staff Engineers, and executive leadership to align technical direction with business strategy and LinkedIn’s infrastructure priorities including Operational Excellence, Modernization, and Efficiency • Advise LinkedIn executives on a broad range of technology, strategy, and operational decisions associated with infrastructure at global scale • Serve as a trusted advisor and mentor to the most senior technical talent across the organization, elevating the engineering bar company-wide • Represent LinkedIn externally as a preeminent thought leader — publishing research, presenting at top-tier conferences, contributing to landmark open-source projects, and engaging with the academic and industry communities • Drive cross-company initiatives that deliver lasting improvements to the reliability, scalability, efficiency, and performance of LinkedIn’s infrastructure — spanning online availability, data integrity, compute utilization, and AI platform readiness • Anticipate and shape the evolution of infrastructure paradigms — including AI-driven operations, autonomous systems, and next-generation compute — that will define the industry over the next decade