The interview process consisted of five rounds, each focusing on different technical and behavioral aspects. 1. Round 1 – Algorithm (Easy/Medium): I was asked to implement a function that receives two integer vectors and returns their intersection. This was a fairly straightforward coding problem focused on correctness and edge cases. 2. Round 2 – Algorithm/Data Structures (Medium/Hard): The second interview involved deleting nodes from a binary tree and returning the resulting forest. This required solid understanding of recursion and tree traversal. 3. Round 3 – Concurrency (Hard): I was asked to implement a concurrent blocking queue. This tested my knowledge of multithreading, condition variables, and synchronization mechanisms. 4. Round 4 – System Design (Easy): No code. This round focused on designing a system to manage a collection mapping integers to strings, and building an index to map strings to integers. A key challenge was ensuring consistency between the collection and the index, especially when the index is built after the collection starts receiving writes—without halting writes during the indexing process. This required careful consideration of data consistency, background processing, and eventual synchronization. 5. Round 5 – Behavioral: The final round was behavioral, with questions about my past experience, challenges I’ve faced, and how I collaborate with others. It focused on alignment with MongoDB’s values and team culture.

The interview process was well organized and flowed smoothly. However, it had quite a few stages, starting with an HR interview to assess my background and skills, followed by a technical interview that included a live coding exercise and several in-depth technical questions. Overall, it was a thorough process that effectively evaluated both technical ability and problem-solving skills.