Interview experience
Airbnb interview experiences covering Recruiter screen, Technical screen, Onsite - Coding (1-2 rounds), Onsite - System design, +2 more. Round-wise notes, common questions, and what candidates report clears each stage.
Airbnb Interview Questions and Answers (2026)
Airbnb operates a global marketplace for lodging and travel experiences connecting hosts and guests worldwide. In India, Airbnb recruits software engineers for teams working on payments, trust and safety, and core marketplace systems used across the platform.
Explore: Interview experience · HR interview questions · Overview · Placement papers · Preparation guide
Overview
Airbnb’s engineering loop runs a recruiter screen, a technical screen, and a 4-5 round virtual onsite - coding, system design, code review, and one or two Core Values interviews - filled mostly through a narrow US new-grad program, not a campus drive.
HR interview questions
Airbnb HR interview questions with sample answer frameworks - motivation, relocation, STAR stories, and culture-fit prompts.
Airbnb interview process at a glance
| Round | Duration | What it tests |
|---|---|---|
| Recruiter screen | ~30 min | Background, motivation, logistics, comp expectations |
| Technical screen | 45-60 min | Live coding (CoderPad) or online assessment (HackerRank/CodeSignal) |
| Onsite - Coding (1-2 rounds) | 45-60 min each | DSA (medium-hard), dynamic programming, product-flavoured problems |
| Onsite - System design | 45-60 min | Scalable, consumer-product system design |
| Onsite - Code review | 45-60 min | Triaging real/pseudo-code for correctness, security, readability |
| Core Values interview (1-2) | 45 min each | Belonging, ownership, ambiguity - via Airbnb’s stated values |
Airbnb technical screen: quick answers
These answers are compiled from public candidate reports, not from an official Airbnb notice. Few India-specific reports are public, and teams differ, so treat the instructions on your own invite as final.
| Question | Answer |
|---|---|
| Is there an online assessment? | Sometimes. The first technical step is either a 45-60 minute live coding screen on CoderPad or a timed OA on HackerRank or CodeSignal. A November 2025 Glassdoor internship report describes no OA, just two 45-minute coding interviews on Zoom and CoderPad plus one 45-minute values interview. |
| How many questions and how long? | Reports vary. One on-campus report describes a single medium string problem; other OAs use a multi-part progressive problem where later parts build on your earlier code. The 90-minute, 2-3 problem figure seen on prep sites is not confirmed by first-hand reports we read. |
| Which platform is it on? | HackerRank in most Glassdoor reports (2018 and 2022 candidates describe medium to hard HackerRank questions); Interview Query also lists a CodeSignal assessment for some candidates. CoderPad is used for live screens. |
| Does it have negative marking? | No report describes any. It is coding-only and scored on test cases. |
| How much is the cutoff? | Not published. In the on-campus report, only candidates who passed every test case were shortlisted, so treat a partial solution as a likely rejection. |
| Does Airbnb run campus drives in India? | Rarely. One on-campus report exists, but most India openings are for experienced engineers, and Airbnb’s main new-grad route is a narrow US programme. |
| What comes after the screen? | A 4-5 round onsite: 1-2 coding rounds, system design, a code review round and 1-2 Core Values interviews. |
Airbnb interview questions by role
These themes come from a GeeksforGeeks on-campus report and the candidate-reported questions already on this page. They show the level and style, not a fixed list.
| Role | Reported questions and topics |
|---|---|
| Campus / new grad | OA: one medium string problem that had to pass every test case. Round 1: Pacific Atlantic Water Flow with full code and complexity. Round 2: project questions plus a vending machine design (select a product, insert cash, return change, handle expiry dates). Then HR. A November 2025 internship loop was two 45-minute DSA rounds (edge cases and complexity) and one values round, with no system design. |
| Software engineer (experienced) | Longest substring without repeating characters and cycle detection on the screen; Cheapest Flights Within K Stops with path reconstruction, a search-results filtering pipeline, product-framed DP and top-K frequent elements onsite; a code review of a pull request for correctness and security. A 2024 India staff-level report on Taro lists top-K with a priority queue, a Nested Integers problem and low-level design for a home-appliance robot; a 2024 Seattle senior report says to practise speed for the code review round. |
| Senior | Listing search and ranking, an availability calendar that never double-books, an events platform with PII and compliance, and handling a read spike during peak booking. |
Asked across every role: Core Values stories (belonging, hosting, ambiguity, scrappiness) that carry as much weight as coding, and clean, readable code rather than a rushed solution.
Recruiter screen
A roughly 30-minute call to confirm background, work authorisation, logistics, and why Airbnb. Recruiters report listening for genuine interest in the mission even at this early stage, not just a rehearsed answer.
Common questions
- Walk me through your resume/current role
- Why Airbnb, specifically, right now?
- What are your compensation expectations?
- Location, notice period, work authorisation
Full behavioural frameworks are on the Airbnb HR interview questions page.
Technical screen
Either a 45-60 minute live coding session on CoderPad with an engineer, or a timed online assessment on HackerRank/CodeSignal. Some assessments use a multi-part, progressive format where an efficient early solution is required to build on for later parts.
Common questions
- Longest substring without repeating characters (sliding window + hashmap)
- Detect a cycle in a directed graph (DFS colouring / topological sort)
- A progressive, multi-level coding assessment building on your own earlier solution
- Explain the time/space trade-offs of your approach
See how real candidates handled this stage on the Airbnb interview experience page.
Onsite: coding rounds
One or two 45-60 minute rounds. Airbnb’s problem bank skews toward dynamic programming and “product feature” style problems - a pricing/filtering pipeline, a text formatter, a booking-flow simulation - more than pure textbook DSA, and community-tracked banks show a noticeably higher share of hard-rated problems than typical big-tech loops.
Common questions
- Cheapest flights within K stops (and variants asking you to reconstruct the path)
- Design/implement a filtering or ranking pipeline for search results
- Dynamic-programming problems framed as a product feature rather than a textbook prompt
- Top-K frequent elements (heap-based)
Round-by-round breakdowns are on the Airbnb interview experience page.
Onsite: system design
A 45-60 minute round on designing a scalable, consumer-facing system - not necessarily “Airbnb clone” trivia, but the kind of latency, data-modelling, and compliance trade-offs a booking/search product actually faces.
Common questions
- Design a search/ranking service for listings
- Design an availability calendar / booking system that avoids double-booking
- Design a user-activity or events platform, with attention to PII and compliance
- How would you handle a sudden spike in read traffic during a peak booking window?
Onsite: code review round
A distinctive Airbnb round: instead of writing new code, you’re handed real or simplified production-style code (or pseudo-code) and asked to review it as if it were a teammate’s pull request. Interviewers weigh whether you catch correctness and security issues first, and whether you calibrate severity instead of drowning the review in style nitpicks.
Common questions
- Review a snippet and flag correctness bugs before anything else
- Identify a security or data-handling issue in the given code
- Explain how you’d phrase a piece of critical feedback to a teammate
- Decide which issues are blocking vs. a “nit” comment
Core Values interview
Airbnb’s most distinctive round. It’s a dedicated behavioural interview - often conducted by someone outside engineering entirely - built around Airbnb’s stated values (Be a Host, Champion the Mission, Embrace the Adventure, Be a Cereal Entrepreneur, Simplify). Multiple candidate reports describe it carrying equal weight to the technical rounds, capable of sinking an otherwise strong loop. Interviewers probe past the headline story with follow-ups (“what did you do versus the team?”) - specificity beats enthusiasm.
Common questions
- Tell me about a time you made someone feel like they belonged, or hosted someone (literally or figuratively) really well
- What does belonging mean to you - have you ever lacked it?
- Describe a time you had to navigate real ambiguity without a clear playbook
- Tell me about a decision that reflected champion-the-mission thinking over a shorter-term win
- Tell me about a scrappy solution when you had almost no resources
- How would you balance a host’s and a guest’s conflicting interests in a trust-and-safety situation?
Sample answer frameworks for each of these are on the Airbnb HR interview questions page.
Airbnb India roles vs the US new-grad programme
Airbnb hires through two quite separate funnels. The US university and new-grad programme is small and highly competitive; Airbnb does not publish its intake or acceptance rate, and recent Glassdoor reports show internship loops of two coding rounds plus one values round. India openings, by contrast, skew towards experienced platform, backend and compliance-tech engineers hired through postings and referrals, with only occasional campus hiring.
This page covers the engineering loop used in both, which is the same shape: a screen, coding, system design, code review and Core Values. If you are a fresher in India, apply to the specific posting and expect the bar of an experienced-hire loop.
Common technical interview questions and answers
Q: How do you solve Cheapest Flights Within K Stops?
This is a shortest-path problem with an extra constraint on edge count, so plain Dijkstra is wrong because the cheapest path to a node may use too many hops while a pricier one stays within budget. The clean solution is a Bellman-Ford relaxation run exactly K+1 times: keep a cost array initialised to infinity except the source at 0, and on each of the K+1 rounds compute a fresh copy from the previous round’s costs, relaxing every edge as newCost[v] = min(newCost[v], prev[u] + weight). Copying the previous round is essential, since relaxing in place would let a single round use more than one new edge. That gives O(K times E) time and O(V) space. The alternative is a BFS or Dijkstra variant where the state is the pair of node and stops used, and you prune a state only when you have already reached that node with both fewer stops and lower cost. Airbnb follow-ups usually ask you to reconstruct the actual itinerary, which needs a parent pointer stored per round.
Q: How do you find the longest substring without repeating characters?
Use a sliding window with a hash map from character to its most recent index. Move the right pointer across the string one character at a time; if the character is already in the map at an index at or after the current left pointer, jump left to that index plus one, which discards the duplicate in a single step rather than shrinking one character at a time. Update the map with the current index and track the maximum of right - left + 1. Each character is visited once, so it is O(n) time, and space is O(min(n, alphabet size)). The common bug is failing to guard the left jump with the check that the stored index is still inside the current window, which lets left move backwards on inputs like abba and gives a wrong answer. Airbnb interviewers frequently extend this to at most K distinct characters, which swaps the map for a count map and shrinks the window while the distinct count exceeds K.
Q: How do you detect a cycle in a directed graph?
Use DFS with three colours. White means unvisited, grey means on the current recursion stack, and black means fully explored. Run DFS from every white vertex; when you reach a neighbour that is grey, you have found a back edge, which is exactly a cycle. A black neighbour is not a cycle, only a previously finished subtree, which is why a simple visited boolean is wrong for directed graphs even though it works for undirected ones. Complexity is O(V + E) time and O(V) space for colours plus recursion depth. The iterative alternative is Kahn’s algorithm: repeatedly remove zero in-degree vertices, and if fewer than V vertices come out, the remainder forms a cycle. For very deep graphs prefer the iterative version, since recursive DFS can overflow the stack.
Q: What is the most efficient way to find the top K frequent elements?
First count occurrences in a hash map, which is O(n). Then, for the general case, push counts into a min-heap of size K, popping whenever the heap exceeds K, so the heap always holds the K largest counts; that is O(n log K) time and O(n + K) space, and it is the right answer when K is much smaller than n. If you want strictly linear time, use bucket sort: create an array of n+1 buckets indexed by frequency, place each key in the bucket matching its count, and walk the buckets from the highest index downwards collecting keys until you have K. That is O(n) time and O(n) space, since no frequency can exceed n. A third option is Quickselect on the count array for O(n) average time but O(n squared) worst case. In a real ranking service you would instead approximate with Count-Min Sketch or Space-Saving when the key space will not fit in memory.
Q: How do you approach a dynamic-programming problem framed as a product feature?
Work in a fixed order rather than pattern-matching. First name the state precisely, in the vocabulary of the product: for a pricing or booking DP that is usually something like the best value achievable considering the first i nights with j promotions used. Second write the recurrence as a decision at the current index, typically take versus skip, and confirm the problem has optimal substructure and overlapping subproblems, or DP is the wrong tool. Third state the base cases and the answer cell explicitly. Fourth compute time and space from the state space times the transition cost, then look for a rolling-array reduction when each row depends only on the previous one, which turns O(n times W) space into O(W). Finally, if asked which specific items or nights were chosen, keep a parent or choice table and backtrack, because the value table alone does not reconstruct the decision. Saying this sequence out loud is what Airbnb interviewers are scoring, since their DP problems are usually a familiar recurrence wearing an unfamiliar story.
Q: How would you design an availability and booking system that never double-books?
Model availability as date ranges per listing and treat the booking write as the single point where correctness matters. The most robust approach is to let the database enforce it: store bookings with a range type and an exclusion constraint, or in a simpler schema hold a unique constraint on the pair of listing ID and date so overlapping nights physically cannot both be inserted. Wrap the write in a transaction at Serializable or Repeatable Read with a SELECT ... FOR UPDATE on the listing row, so two concurrent requests serialise rather than both reading available and both writing. To avoid holding a lock through a slow payment call, split the flow: create a short-lived hold row with a TTL of a few minutes, take payment, then convert the hold into a confirmed booking, and let a sweeper expire abandoned holds. Reads scale separately, since search and calendar views can be served from a cache or read replica with seconds of staleness, and only the final write path needs strong consistency. The trade-off to state explicitly is that optimistic concurrency with a version column gives better throughput but forces the client to handle a retry, while pessimistic locking is simpler but limits write parallelism per listing.
Q: How would you handle a sudden spike in read traffic during a peak booking window?
Layer defences from the edge inwards. Put a CDN in front of anything cacheable, so listing photos and largely static listing pages never reach your origin. Behind it, cache hot search results and listing detail responses in a distributed cache such as Redis with short TTLs, and guard against a stampede where thousands of requests all miss the same expired key at once by using request coalescing or randomised TTL jitter. Add read replicas for the database and route all search and browse queries there, keeping the primary for writes; accept the resulting replication lag for browse but read the primary after a user’s own booking so they see their action. Protect the origin with per-user and per-IP rate limits and a circuit breaker that sheds non-essential calls, and degrade gracefully by serving slightly stale results rather than errors. Autoscaling helps but is too slow for a sharp spike on its own, so pre-warm capacity ahead of a known event and keep enough headroom that scaling has time to catch up.
Q: What do you look for first when reviewing someone else’s pull request?
Correctness and security before anything else, then design, then readability, and style last. On correctness, check the boundary conditions the tests do not cover: empty and single-element inputs, off-by-one loop bounds, null or undefined handling, integer overflow, and concurrency, especially a read-then-write sequence that is not atomic. On security, look for user input reaching a query without parameterisation, missing authorisation checks where the code verifies the user is logged in but never that they own the object, secrets or tokens in logs, and PII written somewhere it should not be. On design, ask whether the change fits the existing abstractions or bolts a special case onto a shared path. Then calibrate severity out loud, marking blocking issues distinctly from suggestions and prefixing genuine style preferences as nits, because an Airbnb code review round scores your judgment about what matters as much as the defects you spot. Phrase feedback as a question about intent rather than an accusation, and say what is good in the change too.
Frequently asked questions about Airbnb interviews
Does the Airbnb online assessment have negative marking?
No report describes negative marking. Airbnb’s first technical step is either a CoderPad live screen or a HackerRank or CodeSignal OA scored on test cases, and in one on-campus report only candidates who passed every test case were shortlisted.
How many questions are in the Airbnb online assessment?
Reports vary: one on-campus OA was a single medium string problem, while other OAs use one multi-part progressive problem where later parts build on your earlier code. Airbnb does not publish a format or cutoff, so check your invite.
What is the Airbnb interview process for software engineers?
Airbnb’s loop usually runs: 1. Recruiter screen (~30 min) - background, motivation, logistics. 2. Technical screen (45-60 min) - live coding on CoderPad, or a timed online assessment via HackerRank/CodeSignal. 3. Virtual onsite (4-5 rounds, often one day or split across two) - one or two coding rounds, a system design round, a code review round, and one or two Core Values interviews. End-to-end timeline is roughly 3-5 weeks.
What questions are asked in Airbnb interviews?
Coding rounds lean medium-to-hard and skew toward dynamic programming and product-flavoured problems - simulate a booking/pricing flow, build a filtering pipeline, or a modified graph problem like cheapest flights within K stops. System design covers scalable, consumer-product systems (search, booking, availability). The code review round hands you real or pseudo-code and asks you to triage correctness, security, and readability. Core Values interviews ask about belonging, hosting, and navigating ambiguity.
How many rounds are there in the Airbnb interview?
Typically 5-6 touchpoints: recruiter screen, technical screen, and a 4-5 round virtual onsite (1-2 coding rounds, 1 system design round, 1 code review round, and 1-2 Core Values interviews). Exact composition varies by team and level, so treat this as a template, not a fixed script.
What is Airbnb’s Core Values interview?
A dedicated behavioural round, often run by a cross-functional or non-engineering interviewer, that carries equal weight to the technical rounds - candidates report it can override an otherwise strong technical performance. It centers on Airbnb’s stated values (Be a Host, Champion the Mission, Embrace the Adventure, Be a Cereal Entrepreneur), with heavy emphasis on “belonging” - expect at least one question about making someone feel included or supported.
How should I prepare for Airbnb interviews?
Drill medium-to-hard DSA with real dynamic-programming reps (Airbnb’s hard problems skew toward involved implementation, not just clever tricks), practise reviewing someone else’s code out loud for correctness/security/readability, be ready to design a consumer-scale system in plain language, and prepare 2-3 STAR stories per Core Value - especially one about helping someone feel like they belonged.
Does Airbnb ask hard dynamic-programming questions?
Yes - community-tracked problem banks show Airbnb sitting above the typical big-tech split, with a noticeably higher share of hard-rated problems and a heavier DP presence than most peers. Problems are also often framed as product features (a text formatter, a pricing/filtering pipeline) rather than pure textbook DP, so practising the pattern isn’t enough - you also need to map it onto a realistic scenario.
How selective is Airbnb hiring?
Very. Airbnb does not publish an acceptance rate, and campus recruiting is limited to a short list of schools rather than a broad drive. Community-reported final-onsite offer rates vary widely by team and level, so treat any single number as a rough signal, not a guarantee - the harder filter is getting to the onsite at all.
Is Airbnb’s process different for freshers vs experienced hires?
Yes. Airbnb’s real entry point is a narrow, US-centric new-grad program (opening dates are not published; watch Airbnb’s careers page) plus referrals, not a college placement drive. Its India offices (Bangalore, Gurgaon) hire actively, but openings there skew toward experienced platform, backend, and compliance-tech roles rather than fresh graduates - verify any India campus-drive claim directly with Airbnb before repeating it.
What makes Airbnb interviews different?
Many loops include a dedicated code review round and one or two Core Values interviews that can outweigh a strong coding day. Prep those as scored rounds.
How long is the Airbnb process?
Roughly 3-5 weeks from recruiter screen through onsite, according to candidate guides, with scheduling variance by team.
Is Airbnb a campus drive in India?
No. Public India hiring for SWE is often experienced-hire oriented; US new-grad programs are separate and highly selective. Confirm the posting you applied to.
What interviewers are scoring at Airbnb
Airbnb loops score practical coding (often DP or product-flavoured), code review judgment, marketplace system design, and a standalone Core Values bar.
| Signal | What a strong answer looks like |
|---|---|
| Coding | Working solution with tests and trade-offs; DP and modeling show up often in reports |
| Code review | You triage correctness, security, and readability under time - not nitpick style alone |
| Design | Booking, search, availability, notifications with clear constraints |
| Core Values | Host / mission / adventure stories with real conflict, not travel slogans |
India hiring skews experienced; treat US new-grad selectivity as a separate funnel.
Behavioural themes to prepare
Core Values themes: Be a Host, Champion the Mission, Embrace the Adventure, Be a Cereal Entrepreneur, Simplify. Prep:
- Hosted someone (onboarding, supporting a guest/user, or mentoring)
- Mistake affecting a customer - fix and prevention
- Cross-functional conflict with design/PM resolved as peers
Frameworks: Airbnb HR interview questions.
How to prepare for Airbnb interviews
- Loop map: Recruiter screen; Technical screen; Onsite - Coding (1-2 rounds); Onsite - System design. Confirm timings from the drive mail.
- Technical depth: Drill the Q&A section until answers are spoken, not read. Know every resume project cold.
- Experiences: Study round-wise notes on the interview experience page - real prompts beat generic lists.
- HR: Three STAR stories + a specific “Why Airbnb?” on the HR page.
A practical Airbnb prep plan
Use this as a default four-week loop before a Airbnb drive. Adjust to your invite timeline.
- Week 1: Timed aptitude + one easy coding problem a day, plus a one-page cs fundamentals sheet. Open the Airbnb previous-year sets on this site and mark which sections ate your time. Write the timing on a sticky note. That number is more useful than a 200-problem LeetCode streak you never timed.
- Week 2: Most Airbnb drives fail people on the first timed paper or OA. Do three timed sits this week. After each one, log every miss in a two-column note: topic and why (slow, wrong formula, bad edge case, panic). The next sit should only add problems from that log.
- Week 3: Technical interviews at Airbnb usually want a clean project story, one or two CS fundamentals, and (if the process has it) a behavioral or values round. Write STAR stories on paper, not in your head. Practise “Why Airbnb?” with one concrete product, lab, or business line - not a slogan.
- Week 4: Two full mocks, then only error-log topics - no new patterns. If you still have energy, redo only the questions you failed in week 2.
10-day crash version: Days 1-4 timed DSA, days 5-7 resume projects + CS fundamentals, days 8-9 mock interviews out loud, day 10 HR STAR stories on the HR page.
Compensation notes
Candidate-reported fresher/early-career packages for Airbnb often cite ₹35-45 LPA SDE band. Treat forum numbers as ranges, not guarantees - confirm the written offer letter for your team and location.
Sources
Interview process details and sample questions on this site are editorially organized from public candidate reports and hiring write-ups, with round structure, prep notes, and company-specific framing added by our team. For round-by-round stories, see the Airbnb interview experience page. For OA papers and coding drills, use Airbnb on placementpapers.app. Screen quick answers and role-wise questions draw on a GeeksforGeeks on-campus Airbnb interview experience, Glassdoor Airbnb interview reviews from 2018 to November 2025 (read via search snippets), Taro’s Airbnb interview experience previews (2024), Interview Query’s Airbnb software engineer guide (search snippet) and the candidate-reported questions summarised on this page.