Rippling QA engineer interviews test automation frameworks, test strategy, CI integration, performance testing, and debugging complex multi-service systems.
All Roles
Software Engineer
Backend Engineer
Frontend Engineer
Full Stack Engineer
Mobile Engineer
Data Engineer
Data Scientist
ML Engineer
DevOps Engineer
DevOps Engineer
Product Manager
SRE
Security Engineer
Engineering Manager
Data Analyst
UX/UI Designer
QA Engineer
coding
Medium
Verified Question
#1
1. [AI Enabled Coding] Card Game
Category: String coding problem# Question You are building a simplified card game where each player has a hand of cards and the higher-rated hand wins. Each hand contains exactly...Input: String
Output: Computed result
coding
Hard
Verified Question
#2
2. [AI Enabled Coding] Design Logger
Category: Array coding problem# Question You need to design a logger library for a new application. The design should be able to allow us to easily add future loggers, like a db...Input: Array
Output: Printed output
coding
Medium
Verified Question
#3
3. [AI Enabled Coding] Food Delivery Company
Category: String coding problem# Question You are building a driver payment system for a food delivery company. The accounting team needs to track how much money is owed to drivers...Input: String
Output: Integer
coding
Hard
Verified Question
#4
4. [AI Enabled Coding] Rule Evaluator
Category: String coding problem# Question You need to build a rule evaluation system for a corporate credit card platform. Managers should be able to create rules that enforce...Input: List
Output: Computed result
system design
Hard
Verified Question
#5
5. Top 5 Rippling System Design Questions
Category: Sliding window system design problemThese are commonly asked system design questions from Rippling interviewsInput: Given input
Output: Computed result
technical
Medium
Verified Question
#6
6. How to pass AI Enabled Coding Rounds From FAANG Interviewer
Category: Algorithm coding problem# Tips For AI Coding Rounds AI coding rounds are not as different from regular coding rounds as you might think. The interviewer still needs to get...Input: Given input
Output: Computed result
coding
Hard
test automation
#1
1. [OA] Test Automation — Build a parallel testing framework for Rippling’s web application.
In order to ensure the quality of our rapidly evolving web application, Rippling needs an efficient mechanism to run UI tests concurrently across different browsers. This will speed up the release cycle while maintaining stability.
Implement a function that facilitates running tests in parallel using Playwright/Selenium.
-
Example 1:
Input:
Output:
Explanation: The first and last test cases passed, while the second test case failed.
Constraints:
-
- Each test case is a valid string representing a test name.
Implement a function that facilitates running tests in parallel using Playwright/Selenium.
-
def run_tests_in_parallel(test_cases: List[str]) -> List[str]: Runs a list of provided test case scripts in parallel and returns their results.Example 1:
Input:
["test_login", "test_dashboard", "test_settings"]Output:
['passed', 'failed', 'passed']Explanation: The first and last test cases passed, while the second test case failed.
Constraints:
-
1 <= len(test_cases) <= 100- Each test case is a valid string representing a test name.
system design
Senior
ci cd
#2
2. [OA] Flaky Test Detector — design a system to identify and manage flaky tests in Rippling’s CI/CD pipeline.
Flaky tests can undermine the reliability of Rippling's software releases. Implement a class that collects results, tracks test history, and flags tests that show consistency in flakiness over time.
-
-
-
-
Example 1:
Input:
Output:
Explanation: The test has failed at least once in its last few invocations, necessitating review.
Constraints:
-
- Up to
-
class FlakyTestDetector:-
def __init__(self): Initializes the detector object.-
def add_result(self, test_id: str, result: bool) -> None: Records the result of a test.-
def is_flaky(self, test_id: str) -> bool: Determines if a specific test is flaky based on its results.Example 1:
Input:
detector = FlakyTestDetector(); detector.add_result('testA', True); detector.add_result('testA', False); detector.is_flaky('testA')Output:
TrueExplanation: The test has failed at least once in its last few invocations, necessitating review.
Constraints:
-
1 <= test_id <= 10000- Up to
1000 results can be recorded for each test.
system design
Senior
caching
#3
3. [OA] LRU Cache — implement the caching layer Rippling uses for frequent API responses.
Rippling's services rely on efficient caching solutions to improve response times and reduce database load. You need to implement an LRU Cache that manages API responses effectively.
-
-
-
-
Example 1:
Input:
Output:
Explanation: Returns 1, as key 1 is present in the cache.
Constraints:
-
-
-
class LRUCache:-
def __init__(self, capacity: int): Initializes the LRU Cache with a specified capacity.-
def get(self, key: int) -> int: Returns the value for the specified key, or -1 if not found.-
def put(self, key: int, value: int) -> None: Updates or inserts the value for the specified key.Example 1:
Input:
cache = LRUCache(2); cache.put(1, 1); cache.put(2, 2); cache.get(1)Output:
1Explanation: Returns 1, as key 1 is present in the cache.
Constraints:
-
1 <= capacity <= 3000-
0 <= key, value <= 10^4.Related Rippling QA Engineer interview prep
Start practicing Rippling questions
Sign up for free to access walkthroughs, AI-generated questions, and more.
Get Started Free