Staff Software Engineer, Capacity Engineering at LinkedIn · Mountain…

Company Description

LinkedIn is the world's 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. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

Job Description

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.

The Capacity & Efficiency Engineering team drives LinkedIn’s end-to-end infrastructure capacity planning and efficiency strategy. We build the data, models, and planning systems that connect infrastructure demand to business growth, attribute costs to the products that drive them, and forecast resource needs across dozens of infrastructure platforms. Our systems are foundational to how Product, Finance, and Infrastructure leadership make decisions on infrastructure investment, capacity allocation, budget planning, and efficiency. By providing a consistent view of demand, supply, and cost, we enable leaders to make informed trade-offs, identify efficiency opportunities, and scale LinkedIn’s infrastructure sustainably.

We are seeking a Staff Software Engineer to join LinkedIn's Capacity & Efficiency Engineering team and play a critical role in building the foundational datasets, models, and tools that power infrastructure visibility, cost attribution, and planning. As a technical leader, you'll set a high bar for technical excellence, mentor engineers, and partner closely with cross-functional stakeholders to lead forward-thinking solutions.

Responsibilities:

• Build and evolve the systems and tools that power LinkedIn’s capacity planning and efficiency platforms, improving how we forecast demand, allocate resources, and optimize infrastructure investment at scale.
• Make efficiency a first-class engineering outcome – build datasets, signals, and planning tools that surface right-sizing, reclamation, and optimization opportunities across the fleet, and translate them into measurable infrastructure savings.
• Set high standards for data quality, correctness, and reliability across the data and models underpinning critical capacity and financial decisions.
• Stay hands-on in the most complex engineering challenges, personally drive critical implementations, and set the technical bar through code and architecture.
• Influence technical strategy across organizational boundaries, mentor engineers, and raise engineering standards beyond your immediate scope.

Qualifications

Basic Qualifications:

• BS/BA in Computer Science or related technical field or equivalent technical experience
• 4+ years of industry experience in software design, development, and algorithm related solutions
• 4+ years of experience programming in object-oriented languages such as C/C++, Java, Go, Rust, Python, Scala
• Professional experience in capacity planning, infrastructure efficiency, or infrastructure cost and allocation systems at scale.

Preferred Qualifications:

• MS or PhD degree in Computer Science or related technical discipline
• 8+ years of experience in software design, development, and algorithm related solutions with at least 5 years of experience in a technical leadership position
• 8+ years of experience in an object-oriented programming language such as C/C++, Java, Go, Rust, Python, Scala
• 4+ years of experience with large-scale distributed systems and client-server architectures
• 1+ years of experience as an architect, or technical leadership position
• Deep understanding of large-scale infrastructure — public cloud (AWS/Azure/GCP) and/or private/on-prem fleets — and the resource and cost models that govern them.
• Experience leading annual and quarterly planning cycles involving Finance, Product, and Infrastructure leadership.
• Experience with large-scale distributed systems and client-server architectures
• Experience with Data Infrastructure tech stacks: Kafka/PubSub systems, Flink, Airflow, ETL framework and distributed storage (HDFS, S3/EBS, Object Storage, Couchbase, or similar)
• Experience leading and influencing within large, matrixed organization

Suggested Skills:

• Software Engineering
• Cloud
• On Premise
• Capacity Engineering
• Distributed Systems

Additional Information

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 $170,000 - $277,000. Actual compensation packages are based on a wide array of factors unique to each candidate, including but not limited to skill set, years & depth of experience, certifications and specific office location. This may differ in other locations due to cost of labor considerations.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For additional 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.

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Fill out an Accommodation request here: https://app.smartsheet.com/b/form/b660a0327d044969abfd7a4e73d15c36

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 LinkedIn's 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: https://lnkd.in/paytransparency.

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Please use this link to access documents that provide information about how LinkedIn handles the personal data of employees and job applicants, as well as the E-Verify Participation Notice and the Department of Justice Immigrant and Employee Rights Section Right to Work posters: https://www.linkedin.com/legal/candidate-portal.