Amazon Interview Preparation: Leadership Principles, the Bar Raiser, and STAR Stories That Work

Amazon runs the most structured interview process among the big technology employers, and the most misunderstood. Candidates prepare algorithms for weeks and then lose the loop on behavioral questions — because at Amazon those questions are not the soft part of the interview, they are the interview. Details vary by team and year, so treat what follows as the publicly described shape of the process.

Leadership Principles are the grading rubric

Amazon publishes a set of Leadership Principles — sixteen at the time of writing — including Customer Obsession, Ownership, Invent and Simplify, Dive Deep, Bias for Action, Deliver Results, and Are Right, A Lot. Interviewers are assigned specific principles to assess, ask for examples from your past, and write up your answers against them. This is not decoration. The written notes are the evidence a hiring decision is made on.

Practically: your stories are scored against a named rubric, so a story with no measurable result, or one where “we” did everything and “I” did nothing, does not register no matter how impressive the project was.

STAR, with data

Amazon expects STAR answers — Situation, Task, Action, Result — and it expects numbers in the Result. “We reduced page load time” is weak; “p95 went from 2.4 seconds to 900 milliseconds and checkout conversion rose about four percent” is the shape they want. Spend most of your ninety seconds on Action, in the first person, and always close with the result and what you learned.

Build a bank of ten to twelve stories before the loop and map each one to two or three principles, so you are never trapped with only one usable example. Include the uncomfortable ones: a decision you got wrong, a conflict with a manager, a deadline you missed, a time you pushed back on a customer request. Those map to Dive Deep, Earn Trust, and Have Backbone, and they are asked for directly.

The Bar Raiser

One interviewer in your loop is a trained Bar Raiser from outside the hiring team, whose job is to protect the long-term hiring bar rather than fill the role. They typically hold significant influence over the outcome. You will not always know which interviewer it is, which is the point: every round gets your full effort, and every story needs to hold up to follow-up questions about details you did not volunteer.

The technical rounds

Engineers still face coding rounds — data structures, algorithms, complexity — plus system design at mid-level and above. What differs is that the behavioral questions are woven through those same rounds, so a technical interview may open with fifteen minutes of Leadership Principle questions before the coding starts. Budget for that; candidates who treat the first fifteen minutes as small talk arrive at the coding problem having already lost points.

A four-week preparation plan

Week one: write your story bank — ten to twelve stories, each with a number in the result, each mapped to principles. Week two: say them out loud, timed to ninety seconds, until you stop reading and start telling. Week three: coding practice with narration, plus system design if you are mid-level or above. Week four: full mock loops that mix behavioral and technical in one session, in English, because switching between the two under time pressure is the specific skill an Amazon loop tests.

The three most common failures

First, stories without a measurable outcome. Second, “we” instead of “I” — the interviewer cannot credit you for a team’s work. Third, running out of examples by round three because the same story got reused with different framing. All three are preparation problems, and all three are fixed by rehearsing out loud rather than by reading the principles one more time.