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Amazon Staff Software Engineer Interview Preparation Guide

Software Engineer
Amazon
Staff
9 rounds
Updated 6/17/2026

Amazon's Staff Software Engineer interview process is a comprehensive 4-8 week evaluation designed to assess technical mastery, system design expertise, leadership qualities, and alignment with Amazon's Leadership Principles. The process progresses from initial recruiter screening through online assessments, technical phone screens, and finally a full-day onsite loop with 5-6 interview rounds. Staff-level candidates face elevated expectations around architectural thinking, cross-team influence, and the ability to mentor senior engineers while solving complex technical problems at scale.

Interview Rounds

1

Recruiter Screening

2

Online Technical Assessment

3

Technical Phone Screen 1

4

Technical Phone Screen 2

5

Onsite Interview Round 1 - System Design

6

Onsite Interview Round 2 - Coding

7

Onsite Interview Round 3 - System Design Deep Dive

8

Onsite Interview Round 4 - Behavioral and Leadership

9

Onsite Interview Round 5 - Bar Raiser Interview

Frequently Asked Software Engineer Interview Questions

Architecture and Technical Trade OffsEasyTechnical
33 practiced
Describe common load balancing algorithms: round-robin, least-connections, and consistent hashing. For each, provide scenarios where it is the best choice and explain trade-offs for session affinity (sticky sessions) versus stateless routing.
Algorithm Design and Dynamic ProgrammingEasyTechnical
65 practiced
Write a DP solution in your preferred language to compute the length of the longest increasing subsequence (LIS) in an array of integers with the straightforward O(n^2) DP. Explain the DP state and recurrence. Also describe why the naive O(n^2) approach can be improved and hint at the n log n approach without implementing it.
Algorithm Analysis and OptimizationMediumTechnical
73 practiced
Design an efficient Sudoku solver using backtracking augmented with constraint propagation and heuristics. Describe practical heuristics (MRV - minimum remaining values, forward checking, least-constraining-value), use of bitmasks for speed, and analyze worst-case exponential complexity vs why real puzzles are solved fast.
Clean Code and Best PracticesEasyTechnical
86 practiced
Write a Python function parse_user(json_obj) that validates a user payload dictionary with keys 'id' (int), 'email' (non-empty string with '@'), and 'age' (optional int >= 0). Implement defensive input checks and raise clear exceptions for invalid input. Keep the implementation concise and testable.
Initiative and OwnershipEasyBehavioral
58 practiced
Behavioral: Describe a time you had to make a decision with incomplete data while owning a project. How did you balance speed vs. correctness, what mitigations did you use, and how did you communicate risk to stakeholders?
Advanced Data Structures and ImplementationEasyTechnical
77 practiced
Compare separate chaining and open addressing (linear probing, quadratic probing, double hashing) for hash table collision resolution. Describe deletion, tombstones, load factor effects, clustering behavior, and which approach is more cache-friendly in practice.
Array and String ManipulationMediumTechnical
61 practiced
Move all zeros in an integer array to the end while maintaining the relative order of non-zero elements. Do this in-place with O(1) extra space. Example: nums=[0,1,0,3,12] -> [1,3,12,0,0]. Provide code and complexity analysis.
Architecture and Technical Trade OffsMediumSystem Design
29 practiced
Design how you'd implement an application-level circuit breaker and the monitoring around it. Describe the metrics to evaluate (e.g., error rate, latency, success count), sliding window semantics, thresholds, and how you would prevent a thundering herd when breakers reset.
Algorithm Design and Dynamic ProgrammingMediumTechnical
56 practiced
Consider an impartial combinatorial game where players alternately remove coins from a pile according to rules defined by a moveset S. Explain how to compute winning and losing positions using DP (or memoized recursion) and how Sprague-Grundy theorem generalizes this to sums of impartial games. Provide a small example to demonstrate computation of Grundy numbers.
Algorithm Analysis and OptimizationMediumTechnical
87 practiced
Write functions to compute factorial(n) for n up to 1e6 that avoid stack overflow. Provide both a recursive (if language supports tail-call optimization) and iterative version in C++ or Python, and discuss time, space, and practicality (overflow handling and big integer concerns).
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Amazon Software Engineer Interview Questions & Prep Guide (Staff) | InterviewStack.io