Sr. Software Engineer, Backend

Pinterest Pinterest · Consumer · Toronto, ON · Engineering, Product and Design (L2)

Senior Backend Engineer role at Pinterest, focusing on building Pinner-facing features and large-scale distributed systems. The role involves leveraging AI tools for faster execution and information synthesis, with a strong emphasis on critical evaluation and verification of AI-assisted work. While AI is mentioned as a partner and tool, 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. Design, develop, and operate large scale, distributed systems and networks
  5. Leverage AI to seek faster execution (i.e. draft, prototype, outline) and explore alternative options (i.e. iterate, compare approaches)

Skills

Required

  • 5+ years of industry backend development experience, building consumer or business facing products
  • Proficiency in common backend tech stacks for RESTful API, online service, 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
  • Experience leading or owning projects, mentoring others, or driving technical thought leadership
  • Experience building & operating large scale distributed systems and/or networks
  • Experience in Python, Java, C++, or Go or another language and a willingness to learn
  • 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

Nice to have

  • deploying and operating large scale workloads on a public cloud footprint
  • Developer Enablement/Productivity or Internal Tooling
  • CI/CD
  • Generative AI/LLMs
  • Spark/Flink/Big Data technologies
  • Data Science/Analytics
  • Building Products or Internal Tools from Scratch

What the JD emphasized

  • high integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables