Engineering Manager Ii, Enterprise AI Solutions

Pinterest Pinterest · Consumer · San Francisco, CA · IT

Engineering Manager II, Enterprise AI Solutions at Pinterest. This role involves leading a team to solve business problems using AI tools, architecting data solutions for ML/AI innovations, and delivering AI-based solutions for business units like Finance, Accounting, Legal, Sales, and Marketing. The manager will mentor engineers, set team vision, and ensure the quality and correctness of AI-driven outputs.

What you'd actually do

  1. Lead a team of employees and contractors focused on solving business problems using AI tools.
  2. Work closely with the existing software engineering teams to develop a seamless and low friction client experience.
  3. Mentor junior engineers to help them grow and develop into the best that they can be.
  4. Motivate and lead your team to show up every day and do their best work.
  5. Collaborate with stakeholders and partner teams across the organization to architect data lake storage and metadata management technologies to unlock big data and ML/AI innovations

Skills

Required

  • 2+ years of experience leading and growing engineering teams
  • strong hands-on background in Python
  • 7+ years of industry experience designing, building, and operating scalable, highly available backend systems
  • owning production-grade infrastructure at scale
  • Proficiency in designing and delivering AI based solutions that solve real world business problems
  • Understanding of business unit challenges and problems, Focused on Finance, Accounting, Legal, Sales and Marketing
  • Experience with cloud infrastructure on AWS and containerized services using Docker and Kubernetes
  • Demonstrated technical leadership and people management experience
  • setting team vision and long-term roadmap
  • mentoring and growing engineers across all levels
  • driving day-to-day execution and engineering alignment
  • partnering cross-functionally to deliver complex, high-impact platform investments
  • Demonstrated ability to use AI to accelerate team execution, system design, and decision-making
  • sound judgment in validating outputs, maintaining quality, and taking ownership of final outcomes
  • Build storage capabilities that efficiently support large-scale ML/AI workloads, including high-throughput data access, schema evolution, and large-scale column backfills
  • Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
  • High integrity and ownership
  • protect sensitive data
  • avoid over-reliance on AI
  • remain accountable for final decisions and deliverables

Nice to have

  • AI interview philosophy
  • AI in our recruiting process

What the JD emphasized

  • AI tools
  • AI based solutions
  • ML/AI innovations
  • use AI to accelerate analysis
  • AI to improve speed and quality
  • over-reliance on AI
  • accountable for final decisions and deliverables

Other signals

  • leading a team of employees and contractors focused on solving business problems using AI tools
  • architect data lake storage and metadata management technologies to unlock big data and ML/AI innovations
  • use AI to accelerate analysis, iteration, experimentation and time to market
  • designing and delivering AI based solutions that solve real world business problems
  • build storage capabilities that efficiently support large-scale ML/AI workloads