Airbnb software-engineering candidates report coding screens and an onsite that may combine coding, system design, technical experience, core values, and pull-request review. Prepare to explain both implementation choices and past engineering work.
$211K
Avg. Base Comp
$470K
Avg. Total Comp
5 rounds
Typical Rounds
5 weeks
Process Length
Airbnb Software Engineer candidates describe a loop that can extend beyond a conventional coding screen. The supplied reports include recruiter contact, technical screening, coding, system design, a deep dive into previous work, a core-values conversation, and pull-request review. Some candidates instead encountered an online CodeSignal assessment or an additional coding interview, so the exact combination of rounds can vary by candidate and level.
Coding reports range from a short implementation problem with harder follow-up requirements to medium- and hard-level algorithm questions. Candidates emphasized explaining an approach, keeping the implementation flexible, and reserving time to test, fix bugs, and address edge cases. One successful candidate also completed a progressive CodeSignal task involving an online storage system. Practice extending working code when requirements change rather than treating the first correct version as finished.
Pull-request review is a recurring distinctive component in these accounts. Candidates described reviewing multiple changes while sharing their screen, which makes prioritization and time management important. Practice identifying correctness and maintainability concerns and explaining why each finding matters.
System-design prompts may use an Airbnb-related domain rather than a generic textbook scenario. For project and values discussions, be ready to explain technical choices, past impact, collaboration, and long-term goals with enough depth for follow-up questions. Passing the onsite may also lead to team matching rather than an immediate final outcome, particularly for senior candidates.
Synthesized from 15 candidate reports by our editorial team.
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Real interview reports from people who went through the Airbnb process.
The unusual part of my Airbnb process came after the onsite: I passed it, but I’m now sitting in the team-matching stage with no senior openings visible on the career portal. I have nine years of experience, and the role was at the senior level, with total compensation around $450K. The onsite result itself was positive, so the remaining uncertainty is not whether I cleared the interview loop but whether and when a suitable team will have an opening.
What caught me off guard was the lack of visible G9/senior postings while I wait. That makes it hard to tell whether the pipeline is moving or whether I should expect new roles to open later in the year. I’ve heard that team matching can take roughly two months even for someone who eventually matches, and that there may be no hiring-manager calls during that whole period. In that case, the candidate was matched to their first team only after the hiring manager had spoken with multiple people in team match.
My takeaway is that passing the onsite is not the final finish line at Airbnb for this level. Be prepared for a potentially quiet and uncertain team-match period afterward, even if your onsite goes well, and keep your expectations realistic about the timing.
Prep tip from this candidate
Plan for team matching to take time after a successful onsite, potentially with little or no communication or hiring-manager calls while you wait.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
| Question | |
|---|---|
| Data Pipelines and Aggregation | |
| Ticket Reservation Locking | |
| String Palindromes | |
| Listing Bookings Aggregation | |
| Payment Data Pipeline | |
| Underpricing Algorithm | |
| Statistically Significant Test | |
| 2nd Highest Salary | |
| Employee Salaries | |
| Merge Sorted Lists | |
| Monthly Customer Report | |
| Bagging vs Boosting | |
| Rolling Bank Transactions | |
| Random SQL Sample | |
| Raining in Seattle | |
| Over-Budget Projects | |
| Delivery Estimate Model | |
| Weighted Keys | |
| Google Maps Improvement | |
| The Brackets Problem | |
| Find the First Non-Repeating Character in a String | |
| Top 3 Users | |
| User Experience Percentage | |
| Hurdles In Data Projects | |
| Job Recommendation | |
| P-value to a Layman | |
| Permutation Palindrome | |
| Maximum Profit | |
| Rectangle Overlap |
Synthesized from candidate reports. Individual experiences may vary.
Candidates report recruiter conversations followed by a technical phone screen or online assessment. Coding has ranged from Airbnb-tagged LeetCode-style questions to time-limited incremental implementation tasks, so clarify the platform and format with the recruiter.
Candidates report data-structures-and-algorithms questions with widely varying difficulty. Explain your approach, complexity, and edge cases while coding, and reserve time to test and correct implementation issues before the round ends.
Some candidates report a system-design conversation plus a deep dive into a major project. Be prepared to discuss requirements, APIs, trade-offs, ownership, mistakes, and the scope of work appropriate to the level you seek.
Candidates report questions about collaboration, ownership, communication, inclusion, and career goals. Use specific examples rather than general claims, and explain your individual role and the result.
Several candidates report reviewing multiple pull requests while sharing their screen. Practice prioritizing findings, managing the clock, and explaining why a comment matters; this component may appear alongside the other onsite interviews.
