Rippling SDE 2 L6 2026
Summary
I completed three coding rounds, a high-level system design round, and a hiring manager round for an SDE 2 role at Rippling, where AI assistance was allowed.
Full Experience
Interview Experience: 3 Coding Rounds + HLD + Hiring Manager (AI Allowed)
I recently completed an interview process consisting of:
- 3 Coding Rounds
- 1 High-Level System Design (HLD) Round
- 1 Hiring Manager (HM) Round
One interesting aspect was that AI assistance was allowed during the coding interviews.
Coding Round 1 - Food Delivery System
This was an object-oriented design implementation question rather than a traditional DSA problem.
Implement methods such as:
RecordDelivery()PayUpto()AddDelivery()
The focus was on:
- Clean class design
- Efficient data structures
- Optimal Time & Space Complexity
This question is available online, so it's worth practicing beforehand.
Coding Round 2 - Rule Evaluation Engine
Given a list of expenses:
Expense - expenseId - tripId - amount - vendorName - vendorType
Implement:
Evaluate(List<Rule> rules, List<Expense> expenses)
Example rules:
- Expenses of a specific category are not allowed.
- A trip cannot exceed a total amount of X.
- Entertainment expenses cannot exceed X.
- Similar business rules.
The interviewer mainly evaluated:
- Extensible design
- Ability to add new rules easily
- Clean OOP principles
- Optimal TC & SC
Coding Round 3 - Article Management System
Implement operations like:
AddArticle()UpvoteArticle()DownvoteArticle()PrintLastKFlippedArticles()
There were a few additional methods as well.
The emphasis was again on:
- Data structure selection
- Efficient updates
- Production-quality code
Suggested Practice
A good practice problem is the Cache System design question.
Important concepts include:
- A single transaction containing multiple operations
- Commit
- Rollback
- Delete
- Maintaining consistency
Fortunately, I wasn't asked this question, but it's frequently discussed.
High-Level System Design (HLD)
Design a Google News-like News Aggregator.
Prepare from two perspectives:
1. News Feed Service
- Feed generation
- Ranking
- Personalization
- Caching
- Pagination
- Scalability
2. News Crawling Pipeline
- Crawling multiple domains
- Scheduling
- Deduplication
- Parsing
- Storage
- Handling failures
- Updating articles
The interviewer can deep dive into any component, so understand the complete architecture rather than memorizing diagrams.
AI Usage Strategy (Allowed)
My approach during the coding rounds:
- Discuss the overall design with the interviewer.
- Explain the classes, APIs, and data structures.
- Write pseudocode.
- Discuss Time and Space Complexity.
- Confirm the approach before writing code.
- Use the LLM to generate the implementation.
- Verify every class, variable, and method.
- Summarize the final solution to the interviewer.
- Answer follow-up questions confidently by referring to the design.
This approach worked well because the interviewer could clearly see my thought process rather than just generated code.
Hiring Manager Round
The discussion focused mainly on:
- Previous projects
- Architecture of systems I worked on
- Design decisions
- Challenges faced
- Why I was looking for a switch
The HM spent considerable time understanding my past work and evaluating ownership and impact.
Overall Preparation Tips
- Practice implementation-heavy OOP design questions rather than only DSA.
- Focus on writing extensible and production-quality code.
- Be comfortable discussing trade-offs, TC, and SC.
- Prepare at least one News Aggregator HLD thoroughly.
- If AI is allowed, use it to accelerate coding - not to replace your design thinking.
Hope this helps someone preparing for similar interviews. Good luck!
Interview Questions (4)
Food Delivery System Design
Design an object‑oriented system for a food delivery platform. Implement methods such as RecordDelivery(), PayUpto(), and AddDelivery(). The solution should emphasize clean class design, efficient data structures, and optimal time and space complexity.
Rule Evaluation Engine
Given a list of expenses (each with expenseId, tripId, amount, vendorName, vendorType), implement a function Evaluate(List<Rule> rules, List<Expense> expenses) that applies business rules such as disallowing certain categories, enforcing a maximum total per trip, limiting entertainment expenses, etc. The design should be extensible to add new rules easily.
Article Management System
Implement a system to manage articles with operations: AddArticle(), UpvoteArticle(), DownvoteArticle(), and PrintLastKFlippedArticles(). The solution should choose appropriate data structures to support efficient updates and retrieval of the most recent K articles with changed vote status.
News Aggregator System Design
Design a Google News‑like news aggregator. Consider two major components: the News Feed Service (responsible for feed generation, ranking, personalization, caching, pagination, and scalability) and the News Crawling Pipeline (handling crawling of multiple domains, scheduling, deduplication, parsing, storage, failure handling, and article updates). The design should be modular and scalable.
Preparation Tips
- Practice implementation‑heavy OOP design questions rather than only DSA.
- Focus on writing extensible and production‑quality code.
- Be comfortable discussing trade‑offs, time complexity, and space complexity.
- Prepare at least one news aggregator high‑level design thoroughly.
- If AI is allowed, use it to accelerate coding – not to replace your design thinking.