Brex Software Engineer Interview Questions
5+ questions from real Brex Software Engineer interviews, reported by candidates.
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Hi, I have an interview for the SWE intern position at Brex coming up and was wondering if anyone could share their experience? Especially for the debugging round? Any help would be greatly appreciate
Brex Interview Technical Round 1
Implement a basic calculator that can perform addition and multiplication based on a string.
## Problem Implement a rate-limited API client wrapper. The client must respect a maximum of `rate_limit` requests per second. If a request fails with a retryable error (HTTP 429 or 5xx), retry up to `max_retries` times using exponential backoff. Non-retryable errors (4xx except 429) should raise immediately. ```python import time class RateLimitedClient: def __init__(self, rate_limit: int, max_retries: int = 3): pass def get(self, url: str) -> dict: """Make a GET request. Returns parsed JSON response.""" pass def post(self, url: str, payload: dict) -> dict: pass ``` ``` Example behavior: client = RateLimitedClient(rate_limit=10, max_retries=3) # 10 requests/sec max enforced internally # On 429: wait 2^attempt seconds, retry # On 500: same retry logic # On 404: raise immediately ``` ## Follow-ups 1. How would you implement a token bucket or leaky bucket to enforce the rate limit? 2. How does jitter in exponential backoff reduce thundering herd problems? 3. How would you make the client thread-safe for concurrent callers? 4. Extend to support request queuing: callers submit requests and await results asynchronously.
## Problem Parse and evaluate algebraic expressions written in English words or natural language form. ## Likely LeetCode equivalent None identified with high confidence. ## Tags coding, strings, parsing, phone
## Problem You are given a list of transactions `(account_id, timestamp, amount)`. Flag any account where the total transaction amount exceeds a daily limit `L` on any single calendar day. Return a list of `(account_id, date)` pairs that were flagged, sorted by account then date. ```python from datetime import date def flag_accounts( transactions: list[tuple[int, int, float]], # (account_id, unix_ts, amount) daily_limit: float ) -> list[tuple[int, date]]: pass ``` ``` Input: transactions = [ (1, 1700000000, 500.0), (1, 1700000100, 600.0), # same day as above (2, 1700000000, 100.0), ] daily_limit = 1000.0 Output: [(1, date(2023, 11, 14))] # Account 1 total on that day = 1100 > 1000 # Account 2 total = 100 <= 1000 ``` ## Follow-ups 1. How do you handle timezone-aware vs. UTC timestamps when grouping by calendar day? 2. If transactions stream in real time, how do you efficiently update daily totals without reprocessing all records? 3. Extend to flag accounts that exceed a rolling 24-hour window, not just a calendar day. 4. How would you write a SQL query to solve this problem instead?
What Brex Looks for in Software Engineer Interviews
Brex Software Engineer interviews are calibrated against the level and scope expected of the role. Across 5+ verified candidate reports on LeakCode, the consistent signals interviewers look for: clear problem decomposition before coding, explicit complexity reasoning, structured handling of edge cases, and the ability to articulate trade-offs between two reasonable approaches.
The discriminator between candidates who advance and candidates who do not is rarely the final correctness of the solution. It is the path to the solution: did you ask clarifying questions, did you state your approach before coding, did you handle edge cases without prompting, and did you communicate your reasoning throughout. Reports tagged "no hire" frequently cite a working solution with poor communication; reports tagged "strong hire" cite clear thinking even when the final solution was incomplete.
How To Use This Question Set
Real interview reports are a calibration tool, not a memorization target. Companies update their question pools every 2-4 months; memorizing exact problems risks misleading you when the interviewer uses a variant. The high-leverage use: identify the patterns that appear repeatedly in Brex Software Engineer reports, practice those patterns on similar (not identical) problems, and use the reports to understand the interviewer's typical follow-up depth.
Filter the questions below by round type, difficulty, and recency. Focus first on reports from the past 6-12 months; older reports may reference questions that have since rotated out of Brex's pool. Reports tagged with quantified difficulty (e.g., "medium-hard") are higher-signal than reports without difficulty tags.
Round-by-Round Expectations
Brex Software Engineer loops typically span 4-6 rounds across phone screens and on-site or virtual on-site interviews. The structure varies by company: some run 1 recruiter screen + 1 technical phone + 3-4 on-site rounds; others run 1 recruiter screen + 1 OA + 4-5 on-site rounds. The recruiter screen is logistics and culture-light; the technical phone screen is medium-difficulty coding; the on-site loop covers coding, system design (at L4+ levels), and behavioral rounds.
Each round is designed to surface a specific signal. Coding rounds: correctness, code quality, complexity reasoning, communication. System design rounds: requirements clarification, design judgment, operational thinking. Behavioral rounds: ownership scope, leadership, ambiguity tolerance, conflict navigation. Strong candidates explicitly hit each signal dimension out loud during the round; weak candidates focus only on solving the prompt.
Common Interview Mistakes At This Combination
Reports tagged "no hire" at Brex Software Engineer commonly cite: jumping into code without clarifying requirements, coding silently for 10+ minutes without verbalizing approach, missing edge cases (empty input, single element, very large input, overflow), and producing a working solution that the candidate cannot explain or refactor when probed. Strong candidates avoid these patterns by following a consistent template: clarify, verbalize approach, code with narration, test with examples.
Behavioral and design rounds have their own failure modes. Behavioral: stories that use "we" instead of "I" diluting individual signal, stories with no quantified outcome, defensiveness when probed about failure. Design: not asking clarifying questions, not stating requirements out loud, designing for a single server when the prompt clearly implies scale, ignoring operational concerns (deployment, monitoring, rollback). These show up in roughly half of Brex Software Engineer interview retrospectives on LeakCode.
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