Build scalable backend systems for Pinterest's user-facing features, collaborating with product and design teams on full development lifecycle including prototyping, testing, and AI-assisted workflows. Requires 2+ years backend experience with RESTful APIs, storage, caching, and strong AI utilization practices.
119k – 245k/yr
Remote2+ YOEBackend Engineering
About the role
What you’ll do
Build out the backend for Pinner-facing features to power the future of inspiration on Pinterest
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
Partner with design, product, and backend teams to build end-to-end functionality
Put on your Pinner hat to suggest new product ideas and features
Employ automated testing to build features with a high degree of technical quality, taking responsibility for the components and features you develop
Grow as an engineer by working with world-class peers on varied and high impact projects
Leverage AI to seek faster execution (i.e. draft, prototype, outline) and explore alternative options (i.e. iterate, compare approaches)
Leverage AI to synthesize information (summarize, distill themes) and automate repeatable tasks (documentation, reporting, QA checks)
What we’re looking for
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
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
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