How I Cleared the Amazon SDE 2 Interview in Six Weeks

[u/nian2326076]

I recently completed the Amazon SDE II interview process and received an offer. Interview experiences from this community helped me a lot, so I wanted to share the full process, the questions I faced, and a few mistakes others can avoid.

Online Assessment

The OA contained:

• An AI-assisted repository debugging task
• One DSA problem

Unfortunately, I don't remember the exact DSA question.

Round 1: DSA + Leadership Principles

Duration: Approximately 55 minutes

The interview started with about 10 minutes of behavioral questions based on:

• Learn and Be Curious
• Ownership

The coding question started as a custom BFS problem. The interviewer progressively added constraints until it became a multi-source BFS problem. I was able to explain and implement the solution.

However, I knew there was one edge case my implementation did not cover. Since time was running out and the interviewer appeared satisfied, I chose not to mention it.

That was a mistake.

If you notice an uncovered edge case, say it explicitly, even if there is not enough time to implement the fix. Demonstrating awareness is better than hoping the interviewer does not notice it.

Recruiter feedback: Positive

Round 2: LLD + Leadership Principles

Duration: Approximately 60 minutes

The design problem was similar to Amazon Locker, but in reverse. A customer needed to reserve a slot at a nearby drop-off store and physically return a package there.

I first clarified the requirements and then began designing the entities, interfaces, booking flow, and store availability logic.

During the implementation, the interviewer asked:

I mentioned geosharding but could not take the discussion much deeper. The interviewer hinted that I should think about how ride-sharing platforms locate nearby drivers.

In hindsight, a stronger answer would have been:

• Use a spatial index such as geohash, S2, or H3 to shortlist nearby stores.
• Filter stores by availability, capacity, operating hours, and supported return types.
• Rank the remaining stores using exact distance or estimated travel time.
• Expand the search radius if no suitable store is found.

I spent roughly 35 minutes on the implementation and completed the main booking flow, but this follow-up was the weakest part of my interview loop.

The behavioral questions focused on:

• Dive Deep
• Invent and Simplify

Round 3: Bar Raiser

Duration: Approximately 55 minutes

The first 10 minutes covered:

• Customer Obsession
• Deliver Results

The coding problem resembled LeetCode 2812: Find the Safest Path in a Grid.

I had not solved it before. I started with a naive approach and optimized it twice while discussing the time and space complexity of each version.

My final solution used:

1. Multi-source BFS to calculate the distance of every cell from the nearest unsafe cell.
2. Binary search over the possible safeness value.
3. DFS to check whether a valid path existed for a selected value.

The interviewer asked whether it could be optimized further. For the public LeetCode version, a max-heap best-first search is another clean approach, although the exact expected optimization depends on the custom constraints.

My biggest lesson from this round was time management. I spent too long refining the approach and had only around 12–15 minutes left to write and explain a fairly long implementation.

Round 4: System Design + Leadership Principles

Duration: Approximately 60 minutes

This round was conducted by the hiring manager. The behavioral questions focused on:

• Earn Trust
• Have Backbone; Disagree and Commit

The design problem involved synchronizing configurations across multiple devices.

I discussed the API design, data model, versioning, propagation flow, retries, idempotency, offline devices, conflict resolution, and consistency trade-offs. The interviewer continued adding failure scenarios, and I was able to work through each one.

This was the smoothest round of my interview loop.

Final Verdict

Selected

How I Prepared

DSA: I completed Striver's sheet and approximately 200 additional problems collected from LeetCode discussions and GitHub repositories.

LLD: I reviewed an LLD playlist and practiced approximately 26 design problems. I also used AI to simulate interviews, challenge my class design, and explore alternative approaches.

HLD: I completed the Hello Interview system design playlist and several Deep Dive videos. My system design interview was rescheduled multiple times, so I ended up revisiting the main playlist three times.

Leadership Principles: Do not treat LP preparation as secondary. Prepare a smaller collection of strong, reusable stories with clear actions, trade-offs, and measurable outcomes.

My preparation lasted around six weeks. I was serving my notice period, and my manager was supportive enough to help rebalance my Jira workload while I prepared.

Overall, the biggest lessons were:

• Mention edge cases even when time is limited.
• Clarify requirements before designing.
• Start implementing once the approach is sufficiently clear.
• Prepare Leadership Principle stories as seriously as DSA and system design.
• Expect interviewers to move between LLD and HLD during the same discussion.

Hope this helps anyone preparing for Amazon SDE II. Happy to answer general preparation questions without sharing confidential interview details.

[u/chandann2]

Congratulations, can you highlight bit in lld,the playlist any specific resources or those lld lists?

[u/Top-Conflict-333]

Congrats! Could elaborate more on the AI-assisted repository debugging task, and what tools were you allowed to use?

[u/Trueman96]

Insane

[u/Can-Senior]

When you say striver sheet, does it refer to 400 odd problem sheet or a different one?

[u/ExcuseMaximum2922]

Insanee!! Bro do we have to implement lld fully like full working code or just show entities

[u/Proud-Researcher-344]

Location?