Software Engineer Ii, Backend

Pinterest Pinterest · Consumer · San Francisco, CA · Engineering, Product and Design (L2)

Backend engineer role at Pinterest focused on building consumer-facing features. The role emphasizes leveraging AI tools for faster execution and synthesis of information, alongside critical evaluation of AI-assisted work. While AI is a partner, the core craft is backend engineering, not AI/ML model development.

What you'd actually do

  1. Build out the backend for Pinner-facing features to power the future of inspiration on Pinterest
  2. Contribute to and lead each step of the product development process, from ideation to implementation to release; from rapidly prototyping, running A/B tests, to architecting and building solutions that can scale to support millions of users
  3. Partner with design, product, and backend teams to build end-to-end functionality
  4. Put on your Pinner hat to suggest new product ideas and features
  5. Employ automated testing to build features with a high degree of technical quality, taking responsibility for the components and features you develop

Skills

Required

  • 2+ years of industry backend development experience, building consumer or business facing products
  • Proficiency in common backend tech stacks for RESTful API, storage, caching and data processing
  • Experience in following best practices in writing reliable and maintainable code that may be used by many other engineers
  • Ability to keep up-to-date with new technologies to understand what should be incorporated
  • Strong collaboration and communication skills

Nice to have

  • 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

  • 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