After an initial campus-style screen, I started with an OA and waited a while for the next steps. Once I cleared it, the process moved through timed rounds that combined coding, role-specific evaluation, and behavioral work.
The first round was a 1-hour virtual interview on a live coding platform. After a brief introduction, I chose C++ when asked which language I preferred. The coding problems included frequency-based sorting, where frequency set the priority and smaller IDs broke ties, plus an array transformation and minimum-cost problem that depended on a greedy observation. Around that stage, the assessment also included an Amazon Leadership Principles work simulation and a feedback and workstyle survey. Because I mentioned related projects, we also discussed GenAI: verifying RAG hallucinations and semantically searching huge log files by using chunking, embeddings, and vector database ideas at scale.
The second 1-hour virtual round focused more on behavioral questions and problem solving. I had to answer Amazon Leadership Principles questions with concrete examples, and the interviewer pushed for specifics instead of vague answers.
The process lasted months and felt consistent but evaluation-heavy. I was not offered the job. The difficult part was not only the coding, but the breadth of the evaluation, especially the way leadership behavior and GenAI topics were combined with technical reasoning.
Location: Hyderābād. Overall feedback: Neutral. Offer status: No offer.
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