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Rippling interview notes, page 5 of 13

Large Enterprises

Most of these Rippling write-ups come from Software Engineers (126), then Machine Learning Engineers (2). The most reported rounds are the technical phone screen (60), the system design round (48), the hiring manager screen (5) and the onsite coding round (5).

128 interview notes · updated Sep 2026

Rippling·Software Engineer·Technical Phone Screen

May 2026
Phone screen for a software engineer role at Rippling. The coding problem was around building a logger system with various handlers, plus a follow-up on search optimization. Interviewer was low-key and the session was pretty straightforward.
  • Design and implement a logger system that supports multiple handlers such as a capitalize handler, an add handler, and similar transformations.
  • Given the logger system you built, how would you efficiently search for a specific keyword across all stored logs?

“I'd seen a version of this floating around before so I wasn't totally blind going in.”

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Rippling·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at Rippling for a software engineer role, focused entirely on designing a hotel booking system. The interviewer went deep on schema specifics and concurrency, which I wasn't fully prepared for.
  • Design a hotel booking system. What are the core functional requirements you'd cover?
  • Walk through the core data model. What entities do you need and how do they relate to each other?
  • How would you prevent double-booking when multiple users try to reserve the same room type at the same time?
  • How do you handle payment processing to make sure a charge isn't applied twice if a request is retried?
  • What are the quantitative constraints you'd design around? Think about QPS, peak load, and database sizing.
  • How would you scale the system to handle read-heavy search traffic and keep availability data fresh?

“I started with the obvious stuff: search by city and dates, view availability, book and cancel.”

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Rippling·Software Engineer·Onsite - System Design / Architecture

May 2026
Did a system design round at Rippling for a software engineer role, centered entirely on building a news aggregator. Thought it went pretty well but got rejected, which I still can't fully explain.
  • How would you design a personalized news feed for users?
  • How would you scale this system to support a global user base?
  • How do you ensure news content stays fresh and up to date?

“This was the core of the whole interview.”

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Rippling·Software Engineer·Technical Phone Screen

May 2026
Rippling SWE screen that was basically a multi-part OOD problem dressed up as a card game. Three progressively harder parts, and they told you upfront to at least get through part two before time ran out.
  • Design and implement a class structure to represent a poker hand and classify it by type (five-of-a-kind, four-of-a-kind, full house, three-of-a-kind, two pair, one pair, or high card). Then extend it to compare two hands, first by hand type and then card by card left to right if types are tied. Finally, given a list of hands with associated bids, sort them by strength and compute total winnings as the sum of each hand's rank multiplied by its bid.

“Three parts stacked into one problem.”

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Rippling·Software Engineer·Technical Phone Screen

May 2026
Rippling SWE interview with a classic hard algorithm problem. The O(log(m+n)) constraint is what separates the people who've seen this before from everyone else, and I was very much in the second group.
  • Given two sorted arrays, find the median of the combined elements without actually merging them, in O(log(m+n)) time.

“I knew the brute force immediately, merge them, find the middle, done.”

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Rippling·Software Engineer·Hiring Manager Screen

May 2026
Hiring manager round at Rippling for a software engineer role. Pretty much a deep dive into your background and a lot of 'so why Rippling specifically' energy throughout.
  • Walk me through your past experience and the work you're most proud of.
  • Why do you want to join this company specifically, and why this role?
  • Tell me about a time you led something significant. What was your role and what was the outcome?
  • What are you looking for in your next role, and how does this opportunity fit that?

“I had a rough outline in my head but the follow-ups kept pulling me off track.”

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Rippling·Software Engineer·Technical Phone Screen

May 2026
Rippling SWE interview centered on building an expense rule engine across three increasingly complex parts. The bar to pass was reaching at least Part 2, which tells you something about how they pace the problem.
  • Given a list of expenses (each with fields like amount, category, employee, and date) and a list of rules (each with conditions and an action like approve or flag), write code to evaluate every expense against every rule and return which rules match each expense.
  • How would you extend the rule engine to handle richer field types, surface match results to users, and deal with edge cases in a real product context?
  • Extend your rule engine so that rules can have compound conditions using AND and OR logic, including nested combinations. Evaluate the resulting boolean expression against each expense.

“The core of the whole interview.”

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Rippling·Software Engineer·Technical Phone Screen

May 2026
Rippling SWE interview focused on OOD with a Logger implementation question. The whole thing was about design patterns, not just getting code to run.
  • Design and implement a Logger class that supports four behaviors: stripping a configured substring from messages before printing, truncating messages to a max character limit before printing, uppercasing the full message before printing, and storing messages internally without printing anything.

“The four sub-requirements are what make this interesting.”

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Rippling·Software Engineer·Technical Phone Screen

May 2026
Rippling SWE interview with a pretty meaty coding problem around prorated pay calculations and caching. The design discussion went longer than I expected, touching on cache invalidation and memory tradeoffs.
  • Given a list of workers each with an hourly rate and a set of time intervals they worked, implement a function `total_pay_at(cutoff)` that returns the total prorated pay across all workers up to a given cutoff hour.
  • How would you design a caching mechanism for `total_pay_at` so that repeated or nearby cutoff queries don't recompute from scratch each time?
  • What happens to your cache if a worker's hours are added or modified after queries have already been made? How do you handle cache invalidation?
  • What are the memory and precomputation tradeoffs in your caching approach?

“The proration part wasn't hard to reason through once I drew it out.”

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Rippling·Software Engineer·Technical Phone Screen

May 2026
Rippling SWE interview with a meaty OOP design problem. The question had way more moving parts than I expected and the discussion went pretty deep into tradeoffs around money precision, concurrency, and idempotency.
  • Design an in-memory Delivery Cost System for a food-delivery company. It should support registering drivers with hourly rates, recording completed deliveries, computing total cost, marking costs as paid up to a given timestamp (with partial-delivery proration), returning unpaid amounts, and finding the max number of simultaneously active drivers in the past 24 hours.

“This looked like a clean OOP question until I started actually thinking through the edge cases.”

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