Rippling Interview Questions — Page 10

Rippling·Software Engineer·Onsite - System Design / Architecture

Jun 2026

Rippling system design round for a software engineer role. The question was a sprawling news aggregator design covering ingestion, personalization, search, storage, and compliance. A lot of ground to cover in one session.

Design a large-scale news aggregator with personalized feeds. Cover ingestion from thousands of publishers, near-real-time delivery, personalized ranking, search, storage layers, multi-region availability, and compliance.

“This thing had like twelve sub-problems stapled together.”

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Rippling·Software Engineer·Onsite - System Design / Architecture

Jun 2026

Rippling system design round focused entirely on building a rules engine for a corporate expense management product. The question had a lot of surface area and pushed into product thinking pretty quickly, which I wasn't fully expecting from a purely engineering interview.

Design a rules engine for a corporate credit card expense system where managers can define policies. You're given a function signature like evaluateRules(rules, expenses) where expenses are dictionaries with string keys and values. The system needs to flag violations for rules like no restaurant expense over $75, no airfare, no entertainment, and no expense over $250. What should the function return for use as an API response?
How would you represent rules in a way that's extensible to hundreds of different rule types, and how would you handle conflicts or precedence between rules?
How would you build auditing and explanation into the system so that flagged expenses have traceable, human-readable justifications?
What product-oriented clarifications would you ask before building this, and how would managers select and manage the rules they want to enforce?
How would you approach performance and scalability for this rules evaluation system as the number of rules and expenses grows?

“I started with the return type question because it felt like the safest entry point.”

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Rippling·Software Engineer·Technical Phone Screen

Jun 2026

Rippling SWE interview focused entirely on a payroll system design problem. Pretty dense question with a lot of moving parts, felt like it was testing whether you could reason about data structures under real constraints rather than just knowing the theory.

You're extending a fast-food delivery payroll system. It needs to register drivers with hourly wages, compute pay for a given shift defined by a start and end timestamp, and track total payroll across all drivers. How do you design this?
Given a cutoff timestamp, how would you mark all wages earned strictly before that point as paid for every driver, and support querying total unpaid wages at any time?
Walk through the data structure tradeoffs: per-driver sorted or linked-list shift records, binary search on timestamps, prefix sums. What do you gain and lose with each approach?

“The setup seemed straightforward at first and I started talking about a simple map from driver ID to wage.”

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Rippling·Software Engineer·Onsite - System Design / Architecture

Jun 2026

System design round at Rippling for a software engineer role. The whole thing was one big question about a corporate card rules engine, and they wanted you to go deep on basically every layer of the stack.

You're building a rules engine for corporate card policies (e.g. no restaurant charge over $75, trip total under $2000). How do you scale it to handle millions of expenses per day across tens of thousands of rules, covering storage, evaluation pipeline, violation tracking, user notifications, and fault tolerance?

“This was basically the whole interview.”

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Rippling·Software Engineer·Technical Phone Screen

Jun 2026

Phone screen for a software engineering role at Rippling. They gave me an AI coding option and I went with it. The problem was a logger system with multiple configurable behaviors, basically chaining together different output transformations.

Design and implement a configurable logger system that supports the following operations: removing all occurrences of a specified substring before printing, truncating messages to a maximum character length before printing, uppercasing the entire message before printing, and storing messages to an internal list without printing. Each operation should produce output when invoked.

“The individual pieces aren't that hard but the real question is how you structure them together.”

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Rippling·Software Engineer·Technical Phone Screen

Jun 2026

Rippling SWE interview that was basically one big design question stretched across the whole session. You had to code it up live and then defend your choices while the interviewer poked at edge cases.

Design and implement a Task Manager class that supports creating tasks, updating their state (todo, in-progress, done), assigning tasks to users, and querying tasks by user, by status, and by due date. Define the full class API and explain the data structures behind each operation.

“This felt manageable at first and then kept expanding.”

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Rippling·Software Engineer·Onsite - System Design / Architecture

Jun 2026

Rippling system design round, one big question about building an event ingestion pipeline that serves both a real-time dashboard and a batch processing layer. Pretty open-ended, which I wasn't fully prepared for.

Design a system that collects user behavior events (installs, clicks, etc.) and supports two outputs: a real-time metrics dashboard with low latency, and a raw event store for large-scale offline batch processing. Walk through your choices for collection, transport, stream processing, and storage.

“The dual-output requirement is what made this interesting.”

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Rippling·Software Engineer·Onsite - System Design / Architecture

Jun 2026

Rippling system design round, one big question about building a centralized log pipeline from distributed sources. Pretty involved scope, they wanted you to think through the full stack from ingestion to query.

Design a log aggregation system that collects logs from distributed sources, transmits them reliably to a central data center, and stores them in a queryable database supporting both recent window lookups and ad-hoc queries over the past 3 months.

“This one sprawls fast.”

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Rippling·Software Engineer·Technical Phone Screen

Jun 2026

Went through Rippling's technical phone screen focused on low-level design. The round felt decent but not clean, some parts ran over time and the code wasn't fully executable by the end. Still waiting on feedback after a week with no response from the recruiter.

Design a system at the class/object level, implementing the required data structures, core methods, and algorithmic logic for a given problem.

“Got through the main design fine.”

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Rippling·Software Engineer·Technical Phone Screen

Jun 2026

Rippling SWE interview that went deep into currency exchange as a graph problem. The question sounds like a finance puzzle but it's really testing whether you can model multi-day path optimization and reason about cycles under time pressure.

You start with a fixed amount in some currency. You're given exchange rates for two consecutive days, each as a list of directed conversion edges with rates. You can do any number of conversions on day 1, then any number on day 2. What's the maximum amount you can end up with in a target currency after both days? Walk through how you'd model it, handle arbitrage cycles, and analyze the time complexity.

“I went straight to Bellman-Ford in my head because 'cycles' and 'rates' screamed arbitrage detection, but the twist is you're maximizing a product along a path, not minimizing a sum.”

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