Senior Manage of Capacity Engineering

Pinterest; United States; Vor Ort; USD 180.000 - 240.000; Vollzeit

Zusammenfassung

Pinterest seeks a Senior Manager to lead Capacity Engineering for scalable, reliable, and cost-aware cloud infrastructure.

You will guide forecasts, capacity requests, allocations, and governance across compute, Kubernetes, GPU infrastructure, and shared platforms, partnering with SRE, Finance, product, and cloud providers to drive strategy and measurable improvements. Strong leadership and strategic thinking are essential.

Qualifikationen

• Experience managing and developing teams for large-scale cloud infrastructure.
• Ability to use AI to improve speed and quality in workflows.
• Strong ownership and data integrity.
• Experience leading cross-functional infrastructure programs.
• Ability to define a 12-18 month strategy and roadmap.

Aufgaben

• Lead the Capacity Engineering portfolio, defining long-term strategy and success metrics.
• Develop CPU and GPU forecasts and supply plans across workloads.
• Guide design and delivery of capacity requests, allocations, and policy.
• Improve utilization and efficiency across Kubernetes-based shared compute platforms and cloud environments.
• Establish trusted capacity metrics and operating practices with stakeholders.
• Collaborate with Infrastructure, SRE, Finance, product, and cloud providers on capacity decisions.
• Plan team structure and recruit senior talent; foster inclusive, high-performing culture.
• Apply AI to accelerate capacity analysis and repeatable workflows with quality checks.

Kenntnisse

Leadership

Forecasting

Capacity planning

AI in operations

Cross-functional

Strategic roadmap

Budgeting & cost

Ausbildung

Bachelor's degree in computer science or related field

Tools

Kubernetes

Cloud platforms

GPU infrastructure

Jobbeschreibung

• Pinterest is seeking a Sr. Manager to lead our Capacity Engineering team. The team ensures that Pinterest’s cloud infrastructure has the capacity it needs while operating reliably, efficiently and with clear financial accountability
• You’ll lead the full portfolio across forecasting and supply, capacity-management systems, compute and GPU efficiency, infrastructure data and governance and capacity operations
• Lead the Capacity Engineering team and establish its 12–18 month functional and technical strategy, roadmap and success measures tied to Infrastructure 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

Experience managing and developing teams that build or operate large-scale cloud infrastructure, distributed systems, compute platforms or resource-management systemsDemonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputsBachelor’s degree in computer science, a related field or equivalent experienceTechnical experience in public-cloud infrastructure, highly available distributed systems, Kubernetes or shared-compute platforms and capacity-management systemsHigh integrity and ownership: you protect sensitive data, avoid over-reliance on AI and remain accountable for final decisions and deliverablesStrong track record of critical evaluation and verification of AI-assisted work, including testing, source-checking, data validation and peer reviewExperience leading cross-functional infrastructure programs and communicating availability, cost and capacity tradeoffs to Engineering, Finance, SRE and cloud-provider stakeholdersExperience 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