Sr. Manager, Capacity Engineering

About Pinterest:

Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.

Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.

At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.

Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.

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.

What you’ll do:

- 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.