About this role

Lead the Capacity Engineering team and establish its 12–18 month functional and technical strategy, roadmap and success measures tied to Infra and company goals.
Develop CPU and GPU forecasts and supply plans that account for workload demand, delivery constraints, cost and reliability requirements.
Guide the design and delivery of capacity requests, reservations, entitlements, allocation policy and infrastructure-data systems.
Improve utilization and efficiency across Kubernetes-based shared compute platforms, GPU infrastructure and other cloud environments while protecting availability and developer velocity.
Establish trusted metrics and operating practices for capacity risk, allocation, infrastructure cost, realized savings and system health.
Partner with Infrastructure, SRE, Finance, product and platform teams and cloud providers to make capacity and infrastructure-investment decisions.
Plan team structure and longer-term headcount; recruit and close senior talent; develop technical leaders; and sustain an inclusive, accountable and high-performing team.
Use AI to accelerate capacity analysis, forecasting, operational investigations and repeatable team workflows while applying judgment and verification to ensure quality.

What we’re looking for:

Bachelor’s degree in computer science, a related field or equivalent experience.
Experience managing and developing teams that build or operate large-scale cloud infrastructure, distributed systems, compute platforms or resource-management systems.
Experience defining a 12-18 month functional and technical strategy tied to organizational goals and delivering results through senior technical leaders across a broad infrastructure portfolio.
Technical experience in public-cloud infrastructure, highly available distributed systems, Kubernetes or shared-compute platforms and capacity-management systems.
Experience leading cross-functional infrastructure programs and communicating availability, cost and capacity tradeoffs to Engineering, Finance, SRE and cloud-provider stakeholders.
Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
Strong track record of critical evaluation and verification of AI-assisted work, including testing, source-checking, data validation and peer review.
High integrity and ownership: you protect sensitive data, avoid over-reliance on AI and remain accountable for final decisions and deliverables.

In-Office Requirement Statement:

We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.

Relocation Statement:

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
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At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
Information regarding the culture at Pinterest and benefits available for this position can be found here.
US based applicants only

Sr. Manager, Capacity Engineering