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rippling·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Rippling SWE interview round where the coding portion was AI-assisted, meaning you could use any tool you wanted but had to talk through your thinking the whole time before letting the AI actually write anything. The question itself was a known problem circulating on forums, but the real variable was the interviewer since follow-ups differed a lot depending on who you got.

Questions Asked (1)

Q1

Design a system to calculate and distribute salary payments for delivery workers, including your choice of data structures and overall approach.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

The twist here is you spend most of the interview just talking.

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AI HintsAI Generated

Suggested Approach

Clarify requirements first (e.g., scale, payment frequency, delivery types), then propose a modular system with a data model for workers, deliveries, and payments, and algorithms for calculating pay (e.g., per delivery, hourly, bonuses). Discuss trade-offs between batch vs. real-time processing, and how to ensure accuracy and idempotency in distribution.

Pro tip: Emphasize idempotency and auditability in payment distribution—use unique transaction IDs and ledger entries to prevent duplicate payments and enable reconciliation. This shows you understand financial systems' critical requirements.

1. Clarify Requirements and Scope

Ask about scale (number of workers, deliveries per day), payment frequency (daily, weekly), pay structure (per delivery, hourly, tips, bonuses), and regulatory constraints. This ensures the design meets actual needs.

2. Design Data Model and Structures

Define entities: Worker, Delivery, Payment, and Ledger. Choose appropriate data structures (e.g., hash maps for worker lookup, queues for pending payments, trees for hierarchical pay rules) and justify choices based on access patterns.

3. Define Calculation Logic

Outline algorithms to compute pay per worker: aggregate deliveries, apply rates, add bonuses/tips, deduct fees/taxes. Discuss handling edge cases like cancelled deliveries, overtime, or multi-currency.

4. Design Distribution Mechanism

Propose how payments are disbursed: batch processing (e.g., nightly) vs. real-time. Include idempotent operations, retries, and integration with payment gateways. Ensure atomicity and consistency.

5. Address Scalability and Reliability

Discuss partitioning (e.g., by worker ID), caching, and asynchronous processing. Mention monitoring, alerting, and reconciliation to handle failures and ensure accuracy.

Key Points to Mention

  • Idempotency in payment processing to avoid duplicate payments
  • Use of a ledger or transaction log for auditability and reconciliation
  • Trade-offs between batch and real-time payment processing
  • Data structures: hash maps for fast worker lookup, priority queues for scheduling payments
  • Handling of edge cases: cancelled deliveries, adjustments, refunds
  • Scalability considerations: sharding by worker or region, use of message queues

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.