Sr. Software Engineer, Android

Pinterest is a platform that inspires creativity and helps users plan memorable experiences. They are seeking inquisitive and well-rounded Android engineers to join their product engineering teams, where they will build features, collaborate with cross-functional teams, and leverage AI to enhance the development process.

Responsibilities:

• Build out Pinner-facing frontend features in Android 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)

Requirements:

• Deep understanding of Android development and best practices in Kotlin and/or Java, e.g. Activity Lifecycle, memory management, etc
• 5+ years of industry Android application development experience, building consumer or business facing products
• 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