Google

I applied for the Google SWE Intern role through the off-campus route and was first contacted for a short recruiter discussion. The call was not really a technical interview. We talked about my projects, programming experience, preferred language for DSA, and some details from my resume. The recruiter also gave me an idea of what to expect in the upcoming technical rounds, so I used the time afterward mainly for DSA preparation. The first technical interview was conducted through a shared Google Doc. The interviewer gave me the problem statement directly instead of spending a lot of time on introductions. The problem was related to trees and graphs, and I had to first explain how I understood the problem before writing any code. I started by discussing a straightforward approach and then worked through the complexity with the interviewer. The interviewer kept asking small follow-ups rather than simply waiting for me to finish the implementation. I had to generate edge cases, explain the traversal, and justify why my optimized approach would work. Once the main solution was clear, I coded it and walked through it with a sample input. The interaction felt more like solving the problem together than being left alone to write code. I was informed that I had cleared the first round and moved to the second technical interview. This one was noticeably more difficult. The problem involved a graph, and I initially wasn't sure whether DFS, BFS, or some form of dynamic programming would be the right direction. I explained my observations out loud and tried a couple of possibilities before settling on the correct representation. The interviewer gave me a small hint when I got stuck. Instead of directly giving me the solution, they asked a question that helped me reconsider the state I was maintaining. That was enough to get me back on track. I eventually derived the optimized solution and coded it. We spent the remaining time discussing complexity and a few edge cases. One thing I had prepared particularly hard for was being able to explain my thought process. In both rounds, the interviewer cared about why I was choosing an approach, not just whether I could type the final code. Recent off-campus candidate reports similarly describe medium-hard coding rounds involving binary trees and greedy/graph-style problems, with follow-up discussion around optimization. After the technical rounds, I was asked to provide additional information and transcripts. I had a final conversation with the recruiter, and eventually received the offer for the internship. The biggest lesson for me was that preparation for Google was less about memorizing solutions and more about becoming comfortable deriving an efficient solution while continuously explaining the reasoning.