Academic snapshot
Marks: 7.0+ CGPA / 70% throughout (candidate-reported)
Degree: B.Tech / B.E. / M.Tech
Backlogs: None active
Year: Final-year and recent grads (~1 year)
Airbnb Placement Papers 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: Online Assessment · Download PDF · Placement Process · Interview Experience · Preparation Guide · Certifications & Career
Who can apply to Airbnb in 2026?
Airbnb is a product marketplace loop. The printed floor is often 7.0 / 70%. Two fully passing OA solutions still decide whether you see an interviewer.
Who this hub is for
- For: Students targeting Software Engineer roles on search, payments, trust and safety, or platform teams in India (Bangalore, Gurgaon) or global remote-adjacent loops.
- Not the same track: Pure sales, support, or host-ops. Those bars do not map to this OA → DSA → design loop.
- Experienced hires: Mid-level loops add deeper LLD and different CTC. Use fresher sections as a base.
On-campus vs off-campus
| Route | What usually changes | What stays the same |
|---|---|---|
| Campus | Batch OA window, college list (IIT/NIT/BITS/IIIT often cited) | Coding bar, interview depth |
| Careers / LinkedIn | Resume screen volume; sometimes no hard published CGPA | Still expect OA + two tech rounds |
| Referral | Better visibility | You still need passing OA code |
Off-campus does not mean easier coding. If your CGPA sits near 7.0, spend energy on mocks, not on hunting a mythical lower cutoff. Referrals help the resume screen. They do not shorten the 90-minute OA or skip Technical 2. Treat a referred invite like any other: two passing solutions, then a booking sketch you can say without notes. Campus lists that cite IIT/NIT/BITS do not make the OA easier for those colleges. The same 90-minute paper shows up off-campus. Prepare the filter, not the brand prestige. A 7.0 with two passing solutions beats an 8.8 that cannot narrate a double-booking.
Degree, projects, and “is 7.0 enough?”
Is 7.0 CGPA enough? It matches the commonly reported floor. A 7.1 with clean timed coding beats a 9.0 that cannot explain a booking state machine. Airbnb has not locked one public cutoff for every drive.
Branches: CS/IT/Electronics dominate. Related streams show up when DSA is solid.
Gaps and backlogs: Active backlogs are a hard blocker. Recent grads within about 1 year are the usual window.
Who usually fits and who struggles: Good fit if you can finish two mediums in 90 minutes, narrate out loud, and tell one belonging story with a metric. Harder path if you only practised LeetCode hard, freeze on “two guests, one night,” or treat managerial as a formality. Branch myth: ECE can clear this loop when DSA is solid. The OA does not care that you are ECE. It cares that two solutions pass.
What helps: One project you can defend, contest signal when real, any internship with ownership. See certifications after fundamentals.
Branch & skills
Preferred: CS / IT / Electronics and related
Languages: Python, Java, C++, JavaScript
Focus: DSA, marketplace design lite
Differentiator: Search / booking / trust sketches
Detailed eligibility criteria breakdown
| Item | Typical expectation (candidate-reported) | Reality check |
|---|---|---|
| CGPA / % | 7.0+ / ~70% across 10th, 12th, graduation | Verify every drive |
| Degree | B.Tech / B.E. / M.Tech | Related computing degrees on many posts |
| Branch | CS, IT, Electronics | Strong DSA can help adjacent branches |
| Year | Final year + recent grads (~1 year) | Intern conversion also appears |
| Backlogs | No active backlogs | Clear them before paperwork |
| Coding languages | Python, Java, C++, JavaScript | Stick to one; Python often preferred |
Airbnb CGPA criteria
The minimum CGPA required is commonly 7.0+ CGPA / 70% across 10th, 12th, and graduation. Treat it as a shortlisting filter when printed.
| Academic Level | Minimum (typical) | Notes |
|---|---|---|
| 10th | 7.0+ / 70% | When the JD lists all three |
| 12th | 7.0+ / 70% | Diploma holders: follow JD |
| Graduation | 7.0+ / 70% | No active backlogs |
| Backlogs | None active | Cleared backlogs generally accepted |
Airbnb placement papers - last few years
Download 2026 Airbnb placement papers
2026 in detail
2025 placement papers
2024 placement papers
Previous year question papers
Comments & Suggestions
What Airbnb previous year papers actually train
Airbnb does not publish one permanent official paper set. Papers on this site are pattern trainers for the first filter and early technical rounds.
| Round (typical) | What to practice |
|---|---|
| Online assessment | Timed accuracy: 2-3 medium-hard DSA in 90 min |
| Technical 1 | Live coding narration + edge cases |
| Technical 2 | Design lite (search/booking) + more DSA |
| Managerial | Belonging, trust, project impact |
| HR | Why Airbnb, location, CTC band |
Themes that keep repeating (2024-2026)
- 2024 cycles: 90-minute OA with 2-3 medium-hard problems. Students who skipped timeboxes left an easy array incomplete while chasing a hard graph.
- 2025 loops: HackerRank/CodeSignal-style coding, then DSA + search/booking chat. Belonging and trust stories show up in managerial more than in 2010s-style pure HR.
- 2026 prep expectation: Keep two complete OA solutions as the pass habit. Design stays fresher-depth (actors, APIs, empty results). Treat PDF packs as pattern catalogs. Interval-merge and calendar overlap keep returning because they map to real booking conflicts. Own the sort-and-scan template, not a memorised “Airbnb tagged” story. If you only drill graphs, you will waste the easy OA item.
How to use one paper set in a single sitting
- Timed: run a full 90-minute mock (2-3 coding prompts) in the language you will use on test day.
- Untimed review: rewrite the cleaner solution; list three edge cases you missed.
- Map each miss to a theme and pull two cousins from coding questions.
- Spend 15 minutes explaining a booking availability or listing search flow out loud.
- Log one STAR belonging/trust story the session reminded you of.
Related problems to practice
| Theme you saw in a set | What to drill next | Why Airbnb asks it |
|---|---|---|
| Sliding window / unique | At-most-K variants | Search / filter UX |
| Graph BFS / DFS | Shortest path, components | Availability graphs intuition |
| Hash maps | Frequency, grouping | Fast lookups in listings |
| Interval scheduling | Merge intervals | Booking calendars |
| Ranking lite | Top-K, heap | Search ranking intuition |
Airbnb hiring rounds in 2026
Airbnb hires freshers through campus cells (IIT/NIT/BITS-heavy lists), the careers site, LinkedIn, and referrals. After resume screen, the shape is product-company: timed OA, two technicals, managerial, HR.
Application methods
Campus recruitment
Through college placement cells. PPT, then OA and interviews on a batch timeline.
Online applications
Apply on Airbnb careers or LinkedIn. Follow the invite for platform and duration.
Referrals
Employee referrals improve visibility. You still need passing OA code.
1. Resume / eligibility screen
Recruiter checks degree, 7.0+ / 70% when printed, backlogs, and year of passing. Projects help when volumes are high. Coding is the hard filter.
2. Online Assessment (~90 min)
Candidate reports commonly describe a 90-minute assessment with 2-3 medium-hard coding problems. Platforms: HackerRank, CodeSignal, or similar.
| Section (typical) | Questions (reported range) | Time feel | Focus |
|---|---|---|---|
| Coding | 2-3 problems | Full 90 min | Arrays, strings, DP, graphs, trees, hashing |
Languages: Python, Java, C++, JavaScript. Pass habit: solve at least 2 completely with solid complexity. Roughly 15-20% of a large OA batch advancing is a common rumour, not a promise.
Student tip: Skim all prompts in 4 minutes. Bank the solvable two. Invent two edge cases before submit.
Example timing for a 90-minute OA
| Minute | Move |
|---|---|
| 0-5 | Skim all statements; mark easy wins |
| 5-40 | Problem 1: restate → brute → optimize → code → tests |
| 40-75 | Problem 2 the same way |
| 75-90 | Problem 3 or harden edge cases |
Deeper OA notes: Airbnb online assessment.
3. Technical interview 1 (~45 min)
Video shared editor. Expect 1-2 DSA problems. Narrate brute force → bottleneck → code → edges. Silent staring after a failed test case is a common reject signal.
4. Technical interview 2 (~45 min)
System design lite plus extra coding if time remains. Typical prompts:
- Booking/availability for a listing
- Search and filter for stays
- Recommendation of similar homes
- Payments idempotency at fresher depth
Worked mini-outline - booking calendar:
- Actors: guest, host, listing, calendar service.
- States: available, requested, booked, cancelled.
- Conflict: two guests, same night: first commit wins or version check.
- Failure: overbook → clear error, refund path in words.
- Scale later: only after the above is clear.
5. Managerial (~45 min)
Leadership, teamwork, conflict, impact. Cultural language: belonging, trust, safety. Tie one resume project to a guest/host problem without forcing the brand.
6. HR (~30 min)
Why Airbnb, Bangalore/Gurgaon relocation, joining date, CTC. Know the ₹35-45 LPA fresher band.
| # | Round | Duration | What they check |
|---|---|---|---|
| 1 | OA | ~90 min | Timed accuracy |
| 2 | Technical 1 | ~45 min | Code + narration |
| 3 | Technical 2 | ~45 min | Design + DSA |
| 4 | Managerial | ~45 min | Belonging, impact |
| 5 | HR | ~30 min | Logistics, integrity |
Timeline from application to offer
| Phase | Typical duration | Notes |
|---|---|---|
| Apply / resume screen | 1-2 weeks | Referrals can be faster |
| OA → shortlist | About a week | Trust the invite |
| Interview loop | ~1-2 weeks | Tech 1 → Tech 2 → Managerial → HR |
| Offer / paperwork | 3-5 days common | Written offer wins over verbal |
| End to end | ~3-4 weeks often | Off-campus can stretch |
How Airbnb differs from a generic SaaS interview
- Marketplace vocabulary (search, calendar, trust) shows up more than retail carts.
- Managerial is a real round, not a 10-minute formality.
- Communication is graded: think out loud.
OA skip rules that save the 90-minute paper
- Skim all 2-3 prompts in 4 minutes. Mark the one you can finish.
- Bank a complete passing solution before opening a hard graph.
- Write two edge cases (empty calendar, overlapping bookings, unicode in names) before submit.
- If stuck at minute 25 on problem 1, leave a brute force that passes samples and move.
- Last 8 minutes: re-run tests, not a new algorithm.
Log every mock: which pattern ate the clock (intervals vs graphs vs DP). That log is the prep plan.
Weekend mock that matches a real loop
Saturday 10:00: 90-minute OA (2-3 medium-hard; two must fully pass).
Saturday 12:00: review misses into an error log.
Saturday 16:00: speak booking calendar + listing search, 90 seconds each, no notes.
Sunday 11:00: 45-minute live coding with a friend or a timer and a shared doc.
Sunday 12:00: Why Airbnb + one belonging STAR + Bangalore/Gurgaon answer, recorded once.
Two weekends of that beat twelve nights of “Airbnb tagged” lists. If your college is not on the visit list, keep the same mock and apply off-campus; the OA bar does not drop.
Documents pack
Resume one page, 10th/12th/degree scans matching the 7.0 story, ID, GitHub or contest links if they are real. Name and percentages must match the form.
Night-before checklist
- Charger, ID, resume PDF
- One language chosen (Python preferred if you are fluent)
- Two STAR stories and the booking sketch already spoken once today
- Sleep. A 9 a.m. OA after a 3 a.m. mock is how easy interval items go wrong
- Confirm video setup if the loop is virtual
Where to practise for Airbnb
Online assessment
OA format, timing, and question types.
Coding questions
DSA patterns for OA and technical rounds.
Aptitude / mock quiz
Quant, logic, and timed mock quiz.
Interview experiences
Candidate stories and round notes.
HR interview questions
Common HR questions, sample answers, STAR tips.
Week-by-week prep
Study plan and round-by-round strategy.
Airbnb prep focus: DSA, design, belonging
Week-by-week calendars live on the preparation guide. This section is the focus split so you do not study like you are sitting a 90-minute mixed aptitude paper.
Time split that matches the filter
| Bucket | Share | What “done” looks like |
|---|---|---|
| Timed DSA / OA | ~45% | Two of three mediums fully passing in 90 minutes |
| Design lite | ~25% | 90-second booking or search sketch |
| Project + belonging STAR | ~20% | Metrics + one trust/conflict story |
| CS one-liners | ~10% | OOP, SQL, HTTP you can say aloud |
If you already clear OA and fail narration, invert 45/20 for two weeks. If you freeze on design, stop hiding in LeetCode hard.
This week, not “someday”
- One full timed mock from coding questions plus online assessment.
- Two medium problems submitted end-to-end in Python or Java.
- Speak a booking calendar sketch once without notes.
- Record “Why Airbnb” once with belonging/trust, not a slogan. Record again.
- Error log: three DSA misses, one design blank, one STAR story.
What not to waste time on
- Memorising “Airbnb tagged” dumps as if they will reappear
- Starting a second language the week of the OA
- Staff-level distributed systems for a fresher cabin
- Belonging essays without two passing OA solutions
- Quoting ₹70-90 LPA staff bands in fresher HR
Belonging stories that do not sound like a brochure
Pick a real conflict: a teammate who shipped a breaking change, a guest-facing bug in a college portal, a time you had to say no to a feature that would have hurt users. Situation, what you did, the metric or the apology. “I believe in belonging” with no story is a reject signal in managerial even after a clean OA.
Trust and safety at fresher depth is not a policy thesis. Example: fake listings, double bookings, payment disputes. Say who the actors are, what you store, and what the user sees when something fails. That is enough.
Search sketch students should rehearse
Listing search for a city + dates:
- Actors: guest, search service, listing index, calendar service.
- Filter: city, dates, guests, price. Empty result is a valid answer; say how you show it.
- Rank: simple relevance (price + reviews + distance) before ML theatre.
- Conflict: listing just booked while results are on screen: stale card, refresh, no silent overbook.
- Scale later: only after the above is clear. Do not lead with Elasticsearch jargon you cannot explain.
Offer-stage discipline
- Read city (Bangalore vs Gurgaon) and hybrid language
- 10th/12th/degree % must match
- Equity/ESOP vesting is on the letter, not on a blog
- Verbal “we loved you” is not an offer PDF
- Do not quote staff ₹70-90 LPA in a fresher negotiation
Extra Airbnb prep notes
If a Airbnb invite is 3-8 weeks out, treat this hub as the map and the linked practice pages as the drills. Do not reread eligibility ten times. Check the JD once, then spend hours on the filter that actually rejects people.
Typical fresher CTC chatter for Airbnb sits around ₹35-45 LPA (candidate-reported - confirm the letter). Languages students mention most often: Java, C++, Python, C. Pick one and stay with it in OA and interviews.
Eligibility reminder (from student reports): Candidate-reported campus floor is often 70% or 7.0+ CGPA across 10th, 12th, and graduation; B.Tech/B.E./M.Tech in CS, IT, Electronics or related fields; final-year or recent grads (within about 1 year); no active backlogs. Strong DSA can matter more than sitting on the 7.0 line. Always verify the careers posting.
What you are training for: Typical fresher loop: Online Assessment (~90 min, 2-3 medium-hard coding) → Technical 1 (~45 min) → Technical 2 (~45 min, design + more DSA) → Managerial (~45 min) → HR (~30 min). Campus and off-campus both appear. End to end often 3-4 weeks.
Short version of the prep split: Split time roughly 45% DSA, 25% search/booking/trust design lite, 20% timed OA mocks, 10% belonging/trust STAR stories. Languages: Python (often preferred), Java, C++, JavaScript. Aim to fully solve 2 of 3 OA problems. Full week plan: /airbnb/preparation-guide/.
A four-week plan that actually gets used
Week 1 - pattern, not vibes. 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 - the steep filter. 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 - talk tracks. 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 - mocks and logistics. 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.
Where the hours should go
| Slice | Share of weekly hours | What “done” looks like |
|---|---|---|
| Timed papers / OA | ~40% | You finish a Airbnb-style sit without guessing the clock |
| Coding / role technical | ~30% | You can explain a solution out loud in your chosen language |
| Fundamentals / domain | ~20% | You can teach one OS/DBMS/networks (or domain) topic to a friend |
| Stories + HR | ~10% | Two STAR stories and a specific Why-this-company answer |
If you only have 10 days, keep the same ratios and cut volume, not the timed sits.
Practice pages to open this week
- OA / assessment notes
- aptitude mock quiz
- coding question bank
- interview experiences
- HR question bank
- week-by-week guide
- previous year papers
- 2026 paper page
Use this hub for the Airbnb story (eligibility, rounds, salary). Use those pages for timed reps and interview notes.
Common ways students waste a month
- Collecting 12 Airbnb PDFs and never sitting one under a timer.
- Switching languages every weekend because a senior used a different one.
- Memorising HR answers before they can finish the OA.
- Ignoring the company-specific quirk on this page (unique round, exam name, or role band) and preparing like a generic service-company drive.
If you do one thing after reading this: schedule three timed Airbnb papers on three different days, then interview prep on the leftovers.
If you are starting from a service-company prep base
A TCS/Infosys aptitude deck still helps the quant/logic slice of many Airbnb papers, but do not assume the same cutoff culture. Read the process section on this page once, then swap in Airbnb-specific coding or domain drills from the nested banks. Shared prep is fine; shared assumptions about rounds are not.
What Airbnb pays freshers (candidate-reported)
Figures below are candidate-reported India bands (as of August 2026). Actual offers depend on level, location (Bangalore, Gurgaon), hiring year, and written components (base / bonus / equity).
| Track | Typical CTC (candidate-reported) | Notes |
|---|---|---|
| Software Engineer (fresher) | ₹35-45 LPA | Primary band for this hub |
| Senior SWE (indicative) | ₹50-65 LPA | Not campus default |
| Staff (indicative) | ₹70-90 LPA | Experience band; ignore for fresher asks |
| Data / PM (entry, rare) | Higher or similar | Not the default campus letter |
Confirm base, joining bonus, and any equity language on the written offer.
Benefits students actually care about
Equity/ESOP language when present, health cover, learning budget (manager-dependent), and relocation when the letter names a city. Hybrid norms: ask; do not assume.
How to talk CTC in HR
Know ₹35-45 LPA fresher context. Ask how the package splits. One calm question beats a staff-band screenshot from a blog.
Equity/ESOP, if the letter includes it, has a vesting schedule. Ask when the first cliff hits and whether the fresher number is CTC including equity at a planning price. Do not treat a ₹70-90 LPA staff blog row as your ask. Bangalore vs Gurgaon can change HRA and tax, not only the office meme.
Payments sketch (fresher depth)
Guest pays for a stay:
- Actors: guest, payments service, listing, calendar.
- Idempotency: the same pay-click must not double-charge. Say you store a request id.
- Failure: card decline → stay not booked; timeout → check status, do not assume success.
- Refund: cancellation policy in words, not a ledger thesis.
- Scale later: only after the above is clear.
That 60-second sketch is enough for Technical 2 if the interviewer pivots from calendars to money.
Recent Airbnb placement trends
Two-of-three OA bar
90-minute 2-3 problem papers still punish incomplete hard attempts.
Marketplace design in Tech 2
Booking, search, and trust show up more than generic URL-shortener-only prompts.
Managerial is real
Belonging and impact stories are graded. Coding still gates the round.
India hubs
Bangalore and Gurgaon remain the usual engineering stories. Confirm the letter.
Net for 2026: do not wait for Airbnb to become an aptitude company. Double down on timed DSA, one booking sketch, and two STAR stories.
Airbnb placement FAQs
Papers & process
Can I download Airbnb placement papers PDF for free?
Yes. Free Airbnb placement papers PDF and 2024-2026 style DSA practice are on this site. Start with the 2026 PDF or the archive.
What is the Airbnb placement process for freshers?
Typical path: Online Assessment (~90 min) → Technical 1 → Technical 2 → Managerial → HR. Campus batches often finish in about 3-4 weeks.
How many interview rounds does Airbnb usually have?
Most fresher SWE loops report five stages. Some invites merge managerial with HR. Count the mailer.
What does the Airbnb Online Assessment look like?
Often 90 minutes with 2-3 medium-hard coding problems. Aim to fully solve two. Details: online assessment.
Eligibility & offer
What eligibility / CGPA do fresher SWE drives usually expect?
Commonly reported floor: 7.0+ CGPA / 70% across 10th, 12th, and graduation; CS/IT/Electronics-related degrees; final-year or recent grads (~1 year); no active backlogs. Your posting overrides this page.
What is Airbnb fresher salary in India?
Candidate-reported Software Engineer CTC often lands around ₹35-45 LPA (as of August 2026). Staff bands in blogs are not campus default. The written offer is the only number that matters.
Do I have to relocate to Bangalore or Gurgaon?
Those are the usual India hub stories. HR checks relocation. Answer honestly.
Prep & Airbnb-specific
How should I prepare for Airbnb?
Split time roughly 45% DSA, 25% booking/search design lite, 20% timed OA, 10% belonging STAR. Details: preparation guide.
Which programming languages are allowed?
Python, Java, C++, and JavaScript are the usual set. Python is often preferred. Do not switch the week of the OA.
What product topics should I revise?
Booking calendars, listing search, recommendations, payments idempotency, and trust/safety at fresher depth: actors, data, bottlenecks, empty results.
How important are belonging stories?
Very in managerial/HR. Coding still decides whether you reach that conversation.
Airbnb vs Uber vs Google for freshers?
All three care about DSA. Airbnb leans marketplace/trust. Uber leans mobility. Google has a larger campus machine. Share DSA; customise sketches.
Any pro tip that actually changes outcomes?
Bank two fully passing OA solutions. Rehearse one booking or search explanation out loud. Communication is part of the grade.
Where can I read real interview experiences?
Start with Airbnb interview experience on this site.
Do I need to solve all three OA problems?
The habit students repeat is two complete, solid solutions. A brilliant third that does not compile rarely saves an incomplete second. Verify your invite for the exact bar.
Is Python required?
No, but it is commonly preferred. Java, C++, and JavaScript also appear. Pick one language you can narrate in. Switching on OA week is how syntax steals minutes.
Airbnb - recent candidate experiences
Fresher SWE loops (2024-2025)
Profile patterns that got selected: B.Tech CSE/IT, roughly 7.0-8.5 CGPA, one internship or a strong project, steady DSA rather than last-week panic.
Online assessment: Timed coding. Clean, fully passing solutions beat partial cleverness. Students who triaged prompts early kept two problems alive.
Technical rounds: Arrays, hashing, graphs, DP. Domain chat around search and calendars. Project deep dive: hardest bug, what you would rebuild, how it would fail at listing scale.
Managerial / HR: Why Airbnb? A time you built trust on a team? Relocation for Bangalore or Gurgaon? Keep answers short: situation → what you did → result.
What hurt: coding before clarifying constraints; treating managerial as HR-lite; staff-level Kafka diagrams; quoting ₹70 LPA in fresher HR.
Story-shaped notes
Story 1 - Selected (CSE ~8.0): OA with two passing mediums → Tech 1 interval-merge with complexity narration → Tech 2 booking state machine in plain English → Managerial conflict STAR. What helped: connecting a college hostel-allotment project to calendars without forcing the brand.
Story 2 - Strong OA, weak design (IT ~7.2): Cleared OA, stalled when asked “what happens if two guests book the same night?” with zero concrete answer. Takeaway: one 90-second conflict sketch is cheaper than another 50 LeetCode hards the night before.
After you clear OA
- Re-solve every miss from your last two mocks cold.
- Speak two STAR stories and one trust/conflict story without notes.
- Sketch booking and search on a blank doc.
- Warm one tree/graph medium in your interview language.
- Sleep and Bangalore/Gurgaon logistics.
What a thin campus list means for your odds
Airbnb does not run TCS-scale volume. If your college is not on the visit list, off-campus and referrals are the path. That is not a softer OA. It is more resume noise in front of the same 90-minute filter. Keep a Google/Uber/Amazon loop warm until the written offer lands.
If you already hold another product offer, compare city, equity language, and joining date vs finals, not only the ₹35-45 LPA midpoint. A classroom “selected” is still one gate short of a PDF.
Peak campus months for many colleges are August-October. Off-campus and referrals run through the year. If your college missed the visit, do not wait until next August to open the careers page. Run the same 90-minute mock, then apply. The OA does not get easier in March.
Waiting week after OA: re-solve every miss cold, speak two STAR stories, redraw booking and search on a blank page, warm one interval or graph medium, then sleep. Opening a new DP pattern the night before Technical 1 is how people fail problems they already knew.
More fresher narratives: Airbnb interview experience.