Standard LC mediums, nothing too crazy. Interviewer was pretty chill and was helpful in pointing me in the right direction when I needed as well. Only thing I would probably change was to study more on graph problems before hand.
Interview questions [1]
Question 1
You are given an 0-indexed integer array weights, where weights[i] represents the weight of the i-th marble, and an integer k.
Your task is to divide the marbles into k bags such that:
No bag is empty.
Each bag must contain marbles from a contiguous range of indices. That is, if a bag includes marbles at indices i and j, then all marbles with indices between i and j (inclusive) must also be included in that same bag.
The cost of a bag that includes marbles from index i to j (inclusive) is defined as weights[i] + weights[j].
The total score of a distribution is the sum of the costs of all k bags.
Return the difference between the maximum and minimum possible scores among all valid distributions.
Applied online and received an Online Assessment. It consisted of two LeetCode-style coding problems with a time limit . The process was straightforward and fully automated with no human interaction at this stage.
Interview questions [1]
Question 1
Solve a coding problem involving array manipulation under a timed online assessment
There were 2 rounds- one DSA round and one HR round.
In the first round they asked me a DP + trees question which was of medium to hard difficulty.
In the second round the interviewer asked me about my resume, my projects, some computer fundamental questions.
I applied through university. I interviewed at Amazon in May 2026
Interview
This was an On Campus opportunity. First was the Online Assessment, which consisted of 2 questions, solved both. Then they scheduled two rounds of mandatory interviews, both focusing on DSA, Problem Solving, Behavioral Questions and GenAI Fluency,
Interview questions [6]
Question 1
The first question was standard Longest Common Subsequence, interviewers expected me to first explain the brute force solution and then move on to the optimal approach.
"Tell me a time when you worked on a problem which was difficult for you".
"How do you use GenAI in your day to day work?"
"Tell me about a project where you've used GenAI"
Given an array, you can do a merge operation where you merge (or sum) two adjacent equal numbers, remove both the numbers, and replace with the new merged number. For example, [3 1 1] becomes [3 2]. Now you can operate infinite number of times, and you need to return the smallest final array after doing all the possible operations optimally, e.g. for [1 1 1 1] the answer will be [4] and not [1 2 1].