I recently interviewed for the Amazon SDE Internship after clearing the Online Assessment (OA). I hope this experience helps future candidates prepare.

Online Assessment (OA)

The process started with an Online Assessment consisting of DSA and coding questions. After clearing the OA, I was invited for two technical interview rounds.

Round 1 (Technical)

The first round began with a discussion about my background and projects. The interviewer then asked several Generative AI concepts, including:

• What is Generative AI?
• Explain Vector Databases and why they are used in GenAI applications.
• What are MCP (Model Context Protocol) servers?
• What is tokenization, and why is it important in Large Language Models (LLMs)?

The interviewer expected conceptual understanding along with practical applications, so I explained these topics with examples from my projects.

DSA Question

• Longest Palindromic Subsequence

The interviewer discussed different approaches, starting from the brute-force solution and gradually moving toward the optimal dynamic programming approach. I was expected to explain the time and space complexity as well.

Round 2 (Technical)

The second round focused more on Data Structures and Algorithms and my previous projects.

The interviewer asked me to explain my projects in detail, including the technologies I used, the challenges I faced, and the design decisions behind my implementation. There were several follow-up questions based on my project work.

DSA Questions

• One question based on Trees.
• One question based on Graphs.

The interviewer was interested not only in arriving at the correct solution but also in my problem-solving approach, edge cases, and complexity analysis.

Overall Experience

The interview was friendly and discussion-oriented. The interviewers gave enough time to think and encouraged me to explain my thought process before writing code.

Preparation Tips

• Be strong with Dynamic Programming, Trees, and Graphs.
• Revise core Generative AI concepts such as Vector Databases, Tokenization, MCP (Model Context Protocol), and LLM fundamentals.
• Know your projects thoroughly, as interviewers can spend considerable time discussing them and asking follow-up questions.
• During coding questions, communicate your approach clearly before jumping into implementation and always discuss time and space complexity.

Overall, it was a great learning experience, and I enjoyed the interview process. Best of luck to everyone preparing for Amazon interviews!