About 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 to help evolve the serving platforms that power Ads and Core experiences. You will lead large-scale, low-latency distributed-system initiatives that make our serving stack more performant, reliable, observable, and easier to extend.
You will work across Ads and Core engineering teams to define durable platform capabilities, modernize frameworks, and unlock faster product iteration with high confidence in production.
What you’ll do
- Set technical direction and lead architecture for major serving-platform initiatives across Ads and Core.
- Build and operate scalable, highly available systems with clear performance, reliability, and efficiency goals.
- Partner with product, ML, infrastructure, and Core/Ads engineering teams to translate complex requirements into reusable platform capabilities.
- Improve the serving stack through framework modernization, API evolution, experimentation controls, observability, and debugging tools.
- Lead complex projects end to end: technical strategy, design, implementation, rollout, adoption, and operational readiness.
- Use AI to accelerate analysis, debugging, design exploration, and iteration while applying sound engineering judgment and validation.
- Raise the quality bar through design reviews, code reviews, documentation, and operational excellence.
- Mentor engineers and scale technical leadership across the organization.