Staff Software Engineer, Ads Measurement Signal

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.

The Conversion Visibility pod enables a performant ads marketplace and helps prove value to advertisers by connecting on-Pinterest intent with offsite conversions in a privacy-preserving way. We are hiring a Staff Software Engineer to lead the backend architecture and implementation of a GenAI-powered Conversion Health agent, using Event Quality Scores and conversion data to proactively detect issues, recommend and automate fixes, and demonstrate measurable performance impact for advertisers.

What you’ll do:

• You’ll operate in a forward-deployed style, partnering directly with internal downstream teams that consume our conversion signal data to understand their workflows, build tailored solutions, and own them end-to-end from design through integration and iteration.
• Own the design and implementation of the Conversion GenAI agent: services, data flows, and retrieval layers that let agents reason over EQS, conversion funnels, and their impact on performance at scale.
• Evolve the existing GenAI Applications: harden prompts and tools, improve retrieval quality, add evaluation and safety checks, and make the agent reliable enough for always-on monitoring and decision support and make the impact on ad performance and efficiency clear.
• Design how the sub-agent connects with downstream ads products (PCL, ROAS bidding) and internal tools, including APIs, contracts, and workflows that surface product‑aware alerts and ranked recommendations to identify opportunities and power perform