Dropbox
Senior
Senior Infrastructure Engineer building Dropbox's next-generation search platform (Dash + file/folder search)
Build a highly scalable in-house search platform that unifies Dropbox Dash (AI-powered work search) with Dropbox's native file/folder search — spanning lexical search, vector search, multi-modal search, Q&A, and recommendations, at an indexing scale of trillions of documents. Requires 9+ years of backend systems experience and comfort owning long-term, ambiguous infrastructure projects.
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What this interview tests
- Scalable indexing architecture for lexical, vector, and multi-modal search
- Unifying two search products into one platform
- Distributed, geographically-dispersed backend systems at trillion-document scale
- Operating system/filesystem/network fundamentals
- Ownership of ambiguous, long-term infrastructure projects
- On-call and production reliability for search services
Common question themes
Design an indexing platform that serves lexical, vector, and multi-modal search from one system
How would you scale a search index to trillions of documents while keeping it fresh?
Tell me about a long-term infrastructure project you owned end-to-end under ambiguous requirements
Describe your experience with search infrastructure like Elasticsearch
How do you approach international expansion for a latency-sensitive backend service?
Walk me through a production incident on a large-scale distributed backend you debugged