Staff Software Engineer, Capacity Engineering
Summary
Staff engineer on LinkedIn's Capacity & Efficiency Engineering team, building the datasets, models, and planning systems behind infrastructure capacity forecasting, cost attribution, and fleet efficiency. Hands-on technical leadership role using OOP languages and large-scale data infrastructure, based hybrid in Mountain View, CA.
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.
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
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.
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