Fellow, Software Engineering- Infrastructure

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 this role you will lead advancements in distributed systems AI-first development and developer productivity while serving as the technical authority for LinkedIns private cloud infrastructure driving efficiency agility and cost attribution at company scale.

Responsibilities

• Define and champion the long-term technical vision and strategy for LinkedIns Infrastructure organization as a whole influencing the direction of LinkedIns 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 LinkedIns 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 LinkedIns 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 LinkedIns infrastructure transformation toward AI-native paradigms evaluating and adopting transformative technologies that position LinkedIns 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 LinkedIns 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 LinkedIns 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

Qualifications :

Basic Qualifications

• Masters or PhD in Computer Science Electrical Engineering or a related field or equivalent exceptional research or industry experience

• 20 years of experience in software engineering with a sustained focus on infrastructure distributed systems Storage databases or related areas

Preferred Qualifications

• Exceptional breadth and depth of expertise spanning multiple infrastructure domains including distributed systems service delivery compute and storage infrastructure data platforms online databases caching and AI/ML infrastructure at scale

• History of defining technical direction for large engineering organizations and influencing industry practices

• Demonstrated ability to anticipate multi-year technical challenges and architect transformative solutions

• Recognized technical authority with a track record of company-wide or industry-wide impact

• Industry recognition through seminal publications patents major open-source contributions or conference keynotes

• Proven ability to mentor and elevate Distinguished Engineers and Principal Staff Engineers

• Strong record of translating deep technical vision into platform and business outcomes at company scale

• Experience leading infrastructure modernization and AI transformation initiatives at large scale

• Experience driving developer productivity at scale including tooling frameworks and platform investments that measurably improve how engineers build test and deploy software across a large engineering organization

• Deep experience driving infrastructure efficiency fungibility and agility at hyperscale including capacity planning cost attribution and compute optimization across large-scale infrastructure environments

• Familiarity with the full infrastructure stack: physical and hardware infrastructure compute orchestration networking storage data processing pipelines online serving systems and AI/ML platforms

• Experience working across open-source communities to participate in and influence cutting-edge projects relevant to infrastructure (e.g. Kubernetes Envoy Kafka or equivalent)

• Experience leading high-impact cross-company initiatives

Suggested Skills

• Distributed Systems Architecture

• Developer Productivity

• Full-Stack Infrastructure Leadership

• AI-Native Infrastructure

• Industry Thought Leadership

• Open Source Leadership

• Data Infrastructure and Platforms

• Reliability Engineering at Scale

• Operational Excellence and Efficiency

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 $335000 to $548000. 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 Information :

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 at and describe the specific accommodation requested for a disability-related limitation.

Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:

• Documents in alternate formats or read aloud to you
• Having interviews in an accessible location
• Being accompanied by a service dog
• Having a sign language interpreter present for the interview

A request for an accommodation will be responded to within three business days. However non-disability related requests such as following up on an application will not receive a response.

LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about discussed or disclosed their own pay or the pay of another employee or applicant. However employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information unless the disclosure is (a) in response to a formal complaint or charge (b) in furtherance of an investigation proceeding hearing or action including an investigation conducted by LinkedIn or (c) consistent with LinkedIns legal duty to furnish information.

San Francisco Fair Chance Ordinance

Pursuant to the San Francisco Fair Chance Ordinance LinkedIn will consider for employment qualified applicants with arrest and conviction records.

Pay Transparency Policy Statement

As a federal contractor LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: Data Privacy Notice for Job Candidates

Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: Work :

No

Employment Type :

Full-time