Primary record

Staff Software Engineer, Capacity Engineering

Pinterest Indexed employerSan Francisco, CA, US; Remote, US · San Francisco, CA, US
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Workplace

remote

Employment

Internship

Published

Aug 11, 2026

Closes

No date supplied

The role

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 Staff Software Engineer, Capacity Engineering. The team is responsible for efficiently managing one of the largest-scale cloud-native infrastructures in the world. This role is highly impactful, as efficiency is an ongoing strategic priority for Pinterest. The role has direct visibility across Pinterest Engineering and with Engineering and company leadership. The team is looking for a candidate with a strong background in implementing performance and efficiency projects on large scale distributed systems. In this individual-contributor role you will own and drive performance and efficiency for a co

Requirements

Department: Data Engineering