Dropbox
32 questions · 16 experiences · LeetCode (33) · 1p3a (8) · Other (7)
48 entries
1/2Dropbox Infra Software Engineer Metadata Online Assessment Experience
Dropbox | Online Assessment | Banking Syste,
Dropbox Onsite
Dropbox @ Quality Engineer phone screen
Dropbox | Sr. Software Engineer | San Francisco [Reject]
Dropbox | OA 2019 | Auto-complete feature
Dropbox | Phone Screen | Permissions in a File System
Dropbox | Phone Screen | Implement getByClassName & getByClassnameHierarchy
Dropbox | Phone Screen | Senior Software Engineer | Reject
Dropbox OA | Insanely Hard
Dropbox | Rate Limiter
Dropbox Interview Telephonic + Onsite
Dropbox | Phone Interview | Reject with interesting experience!
Dropbox | Pattern Matching
Dropbox | OA2 Internship
Dropbox Internship Phone Interview
Dropbox phone interview
Dropbox OA - CodeSignal - Cutoff Cases?
Dropbox System Design Round
Dropbox | Design Hit Counter
Dropbox | Game of Life
Dropbox | Phone Screen | Find Duplicate File in System
Anyone seen Dropbox cloud storage codesignal?
Dropbox | Phone | Add a list of subviews into a parent view of given size
DropBox OA Text Editor
Dropbox Infra Software Engineer Metadata Online Assessment Experience
Question Details
Applicants for the Dropbox Metadata Software Engineer role should be aware of a significant discrepancy between the position's infrastructure focus and the content of the Online Assessment (OA). While the job entails reliability engineering and on-call duties, the one-hour "advanced question" assessment strictly evaluates specific API framework development. Upon selecting a programming language, candidates are presented with a complex, pre-built API framework—such as ASP.NET for C#, Spring for Java, or Django for Python—connected to a React frontend and real backend files. The assessment consists of four progressively difficult questions, requiring the candidate to modify the code and ultimately add a new service. Due to the strict one-hour time limit and the complexity of the stack, the assessment relies heavily on the use of an embedded AI chatbot within the Codility platform. The implicit expectation is that candidates will use prompt engineering to navigate the codebase and generate implementation logic (e.g., asking the bot "how to add a new API to this service"). Consequently, the test evaluates the ability to use AI tools for rapid feature implementation rather than fundamental technical problem-solving skills relevant to infrastructure.