Anthropic·Software Engineer·Onsite - Coding / Algorithms·Senior

SeniorPrefer not to say

May 2026

Summary

Coding round for a Software Engineer role at Anthropic. The problem was a multi-level in-memory banking system simulation, basically building up a fake bank from scratch with accounts, transfers, payments, and eventually account merging. Four levels of increasing complexity, all in one session.

Questions Asked (1)

Design and implement an in-memory banking system that processes a time-ordered stream of operations. Start with account creation, deposits, and balance queries, then layer in transfers, a spending leaderboard, deferred cashback payments, and finally account merging.

Algorithms & Data StructuresSystem DesignData Modeling

Author's notes

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Suggested Approach

Start by clarifying requirements and defining the core data model (accounts, balances, transactions) before writing code. Implement incrementally: first handle account creation, deposits, and balance queries; then add transfers, leaderboard, deferred cashback, and merging, ensuring each layer integrates cleanly. Use appropriate data structures (hash maps, heaps, queues) and discuss trade-offs (time/space complexity, consistency) as you go.

Pro tip: Proactively discuss edge cases (e.g., insufficient funds, duplicate account IDs, merging accounts with pending cashback) and how you'd handle them; this shows production-level thinking. Also, mention that you'd write unit tests for each feature to ensure correctness and catch regressions as complexity grows.

1. Clarify Requirements and Constraints

Ask questions to understand expected operations, data volume, concurrency needs, and performance requirements. Confirm assumptions about account uniqueness, transaction atomicity, and cashback rules.

2. Design Core Data Model and Structures

Define classes/structures for Account, Transaction, and the overall BankingSystem. Choose data structures (e.g., hash map for accounts, priority queue for leaderboard) that support required operations efficiently.

3. Implement Incrementally, Testing Each Feature

Start with account creation, deposit, and balance query. Then add transfer (with balance checks), leaderboard (track spending per account), deferred cashback (schedule future credits), and account merging (combine balances and histories).

4. Analyze Complexity and Trade-offs

For each operation, state time and space complexity. Discuss alternatives (e.g., using a balanced tree vs. heap for leaderboard) and justify choices based on expected usage patterns.

5. Review and Extend

Summarize the solution, mention potential extensions (e.g., persistence, concurrency, error handling), and invite feedback. Ensure all requirements are met and edge cases are addressed.

Key Points to Mention

Use of hash maps for O(1) account lookup and updates.
Priority queue (max-heap) for efficient leaderboard queries, with lazy deletion or updates for spending changes.
Deferred cashback: use a queue or scheduler to process future payments, ensuring they are applied even if account is merged.
Account merging: combine balances, transaction histories, and pending cashbacks; handle ID remapping and potential conflicts.
Time and space complexity analysis for each operation, and trade-offs between different data structures.
Edge cases: insufficient funds, duplicate account creation, merging accounts with pending cashback, and concurrency (if applicable).

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