Manager II, Trends Engineering

What you’ll do

• Lead and grow a team of engineers building Pinterest Trends, Audience Insights, and the next generation of AI-powered advertiser insights products.
• Translate the team's vision into a cohesive roadmap and delivery plan, sequencing key 2026 bets such as Trends Digest, Moments, Topics expansion, Product Attributes, and the audience-first platform foundation.
• Drive measurable advertiser impact by establishing a North Star tied to adoption, insight quality, and incremental ad spend and by standing up the instrumentation needed to prove it.
• Partner closely with Product, Design, Data Science, and peer Ads org teams to embed insights and recommendations into Ads Manager, seller workflows, and other advertiser journeys.
• Set the technical bar for LLM-powered capabilities (summarization, classification, conversational insights, agentic review) with strong safety, quality, and evaluation guardrails.
• Hire, mentor, and retain senior and staff engineering talent, and build team operating rhythms (planning, reviews, on-call, quality bars) that scale with the charter.
• Use AI to accelerate planning, technical exploration, and decision-making across the team drafting strategy docs, comparing architectural approaches, and synthesizing research faster while applying judgment and verification to ensure correctness and quality.
• Use AI to automate repeatable management tasks like status reporting, document synthesis, and review workflows, freeing the team to focus on higher-leverage work.

What we’re looking for

• Bachelor's degree in Computer Science, a related field, or equivalent experience.
• 8+ years of software engineering experience, including 3+ years managing teams of 5+ engineers.
• Experience leading engineering teams that build and ship consumer-facing products.
• Experience managing engineers across multiple levels and helping teams improve in effectiveness, quality, and impact.
• Strong people leadership skills, including coaching, feedback, performance management, and team development.
• Strong product sense and strategic thinking, with the ability to translate broad goals into clear priorities and execution plans.
• Solid technical foundation and the ability to engage in architecture, design reviews, and technical trade-offs.
• Proven ability to lead through ambiguity, align cross-functional stakeholders, and deliver meaningful results.
• Expertise in using data and experimentation to inform product and engineering decisions.
• Demonstrated ability to use AI to improve speed and quality in day-to-day work for relevant outputs.
• Strong track record of critically evaluating and verifying AI-assisted work through testing, review, or other quality controls.