Key skills
AIMLAgenticA/B Testing
About this role
Dropbox is a global community shaping the future of work through innovative technology solutions. The role involves designing and implementing scalable backend systems to enhance media-rich experiences and integrating AI capabilities into Dropbox's core offerings.
Responsibilities:
- Design and implement scalable backend systems that power intelligent, media-rich experiences within Dropbox
- Own complex, ambiguous technical problems and drive them from definition through delivery in partnership with Product and Design
- Serve as a technical DRI for high-impact initiatives within the team, shaping technical approach and execution plans
- Be a hands-on contributor who implements critical and foundational components while setting a high bar for code quality and maintainability
- Contribute to shared APIs and system abstractions that enable new product capabilities and operate reliably at large scale
- Influence technical decisions across collaborating teams, contributing to alignment while maintaining strong engineering standards in a virtual-first environment
Requirements:
- BS, MS, or PhD in Computer Science or a related technical field involving coding (e.g., physics or mathematics), or equivalent practical experience
- Minimum of 9 years of professional experience as a software engineer
- Experience working on consumer-facing product teams and owning delivery of user-facing features at scale
- Experience collaborating cross-functionally with Product, Design, and partner engineering teams
- Ability to work independently in ambiguous, fast-moving environments while making pragmatic technical tradeoffs
- Experience integrating AI or ML capabilities into production products and shipping to customers
- Demonstrated 0→1 experience building and launching new product features or systems
- Experience working with media systems (video, audio, large-scale file processing)
- Experience integrating ML/AI APIs (e.g., LLMs, semantic search, tagging systems, agentic workflows) into production systems
- Experience with experimentation frameworks (A/B testing, metrics-driven product iteration)
- Experience designing internal APIs or shared platform abstractions
- Experience leveraging modern AI tools to accelerate development workflows