Engineering Manager (Innovative Ad Formats)

Join Pinterest as an Engineering Manager I, where you will lead a high-impact team focused on building and supporting mid-funnel ad products. You will be responsible for driving the technical direction and execution of revenue-critical products, applying AI to enhance prototyping and experimentation, and fostering a healthy team culture. This role requires a strong technical background, experience in leading engineering teams, and exceptional collaboration skills.

• Lead an engineering team in the development and support of Pinterest's mid-funnel ad products, ensuring projects are well-scoped, de-risked, and shipped on time.
• Drive initiatives to apply AI across mid-funnel ad products, using AI to accelerate prototyping, experimentation, and iteration while maintaining quality and safety.
• Define the technical roadmap, architecture, and long-term vision for the workstream, and actively contribute code and lead implementation of key projects.
• Bachelor’s degree in Computer Science, a related technical field, or equivalent experience
• 5+ years of industry experience building complex and user-facing products, with clear accountability for timelines, quality, and business impact
• 1+ years of experience leading or managing engineering teams, including setting direction, driving execution, and supporting team members’ growth
• Strong track record of critically evaluating AI-assisted work through testing, source-checking, data validation, and peer review; you know when to trust, when to verify, and when to override
• Exceptional collaboration skills with cross-functional partners, with the ability to navigate ambiguity, make tradeoffs, and keep stakeholders aligned on priorities and progress
• Strong hands-on technical background in ads or similarly high-scale domains, including designing and implementing core components in production
• High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain fully accountable for final decisions, shipped systems, and team outcomes
• Demonstrated experience using AI to improve speed and quality in your day-to-day engineering workflow (e.g., prototyping, code generation, test creation, documentation), with a clear approach to validating accuracy and robustness