Sr. Manager, Engineering, Ad Formats

Pinterest Pinterest · Consumer · San Francisco, CA · Monetization

This role is for a Sr. Manager, Engineering on the Ad Formats team at Pinterest, focusing on leading the development of a next-generation server-driven UI framework for Ads Personalization and Creation. The role involves managing a team of 15 engineers and making key architectural decisions. While the role requires strong knowledge of AI/ML technologies and using AI to improve workflows, its core function is in building and managing software engineering for ad formats, not in developing core AI models or systems.

What you'd actually do

  1. You will be responsible for building our next generation server-driven UI framework to enable Ads Personalization, our Ads Creation interfaces, and the Pinterest Custom Browser.
  2. You will manage a team of 15 multidisciplinary engineers.
  3. Be hands-on, working to provide the highest impact for your team and modeling servant leadership.

Skills

Required

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
  • 9+ years of software engineering experience, including 5+ years of Ads experience.
  • 5+ years of engineering management experience
  • A history of successfully taking user facing features/functionality and delivering end-to-end project.
  • Strong knowledge of and experience implementing AI/ML technologies, mathematics, and statistics.
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review).
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.

What the JD emphasized

  • Strong knowledge of and experience implementing AI/ML technologies, mathematics, and statistics.
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
  • Strong track record of critical evaluation and verification of AI-assisted work (e.g., testing, source-checking, data validation, peer review).
  • High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.