Atlassian SDE Bangalore 2023: Staff Engineer at LocoNav, Karat Screening, Snake Game LLD, Rejected

TL;DR. Gagandeep Singh, Staff Software Engineer at LocoNav India (~6 years at LocoNav, previously at Josh Technology Group), interviewed for Senior SWE at Atlassian Bangalore in November 2023. Passed the Karat screening round (4 out of 5 system design debugging problems, 2 DSA problems on Coderbyte in Ruby). Then Round 2: a ballot-counting DSA problem with weighted prioritization, where the problem statement changed twice during the round and the candidate needed hints. Rejected. Never progressed to the Snake Game LLD, System Design, Values, or Management rounds. The candidate's own assessment: 2 weeks of prep and 30 to 40 easy/medium problems was insufficient for Atlassian's bar.

This is not an "Atlassian interview preparation roadmap." This is one specific Staff-level engineer's experience with Atlassian's 6-round process, showing exactly where the process ended and why 8 years of production experience did not compensate for insufficient DSA preparation.

Why Atlassian's Karat round filters most candidates

Atlassian outsources its first screening round to Karat, a third-party technical interviewing company. The Karat round is not a phone screen with an Atlassian engineer. It is a structured 1-hour assessment conducted by a Karat interviewer on the Coderbyte platform.

The Karat format is distinctive:

The system design debugging segment is not traditional system design. You are given 5 pre-built system descriptions with bugs or architectural flaws, and you must identify the issue in each. The pace is aggressive: 4 minutes per scenario. The pass threshold is 60%, meaning 3 out of 5 correct.

The DSA segment is standard: 2 problems, 30 minutes, any language. The candidate used Ruby.

Why does Atlassian outsource this round? Scale. Atlassian receives thousands of applications for India positions. Having Atlassian engineers conduct initial screens is not scalable. Karat provides calibrated interviewers who follow a standardized rubric, allowing Atlassian to funnel a large applicant pool through a consistent first gate.

The trade-off: Karat interviewers are professional interviewers, not Atlassian product engineers. They cannot answer questions about Atlassian's tech stack, team culture, or specific projects. If you ask "what is the team like?", you will get a non-answer.

Who applied

The seniority gap is the first thing to notice. The candidate was a Staff SWE (typically IC5/IC6 equivalent) applying for a Senior SWE role (P50, typically IC4 equivalent). This is a downlevel move. Companies like Atlassian do not auto-match your current level to their leveling system. If you are a Staff engineer at a 500-person startup, Atlassian may still interview you at P50 and assess whether you meet their Senior bar.

The choice of Ruby is also noteworthy. Atlassian's engineering stack is primarily Java, Kotlin, TypeScript, and Python. Ruby is acceptable for the Karat and DSA rounds (you can use any language), but it may cause friction in LLD rounds where the interviewer expects familiarity with the language's ecosystem and standard libraries. The candidate encountered exactly this issue.

Round 1: Karat Screening (1 hour)

System design debugging: 4 of 5 correct

The candidate answered 4 out of 5 system design debugging scenarios correctly, which exceeded the 60% pass threshold (3 of 5). The exact scenarios were not detailed in the source post, but the format is consistent across Karat assessments: you receive a written description of a system, identify the architectural flaw, and articulate the fix.

DSA: 2 problems (easy + medium)

Two data structure problems on Coderbyte, solved in Ruby. The easy problem took approximately 10 minutes, the medium approximately 20 minutes. Both completed within the 30-minute window.

Result: Passed. Advanced to Round 2.

The Karat round is the easiest round in Atlassian's process. Passing it does not mean you are competitive for the role. It means you are not a false positive in the application pool. The real evaluation begins in Round 2.

Round 2: Data Structures (45 minutes), the rejection round

The interviewer

Senior Software Engineer at Atlassian Bangalore, approximately 2 years tenure. Conducted via Coderbyte.

The problem: Ballot counting with weighted prioritization

The problem involved counting ballots (votes) with some form of weighted priority system. The exact problem statement was not reproduced verbatim in the source, but the candidate described it as a medium-to-hard DSA problem requiring custom comparator logic.

What went wrong

Three issues compounded in this round:

1. The problem statement changed twice. The interviewer modified the requirements during the round, either clarifying ambiguities or adding constraints. In either case, the candidate had to re-evaluate their approach mid-implementation. This is not unusual in Atlassian interviews: interviewers sometimes adjust the problem to test adaptability, but it can destabilize a candidate who has already committed to an approach.

2. The candidate needed hints. The source post states this directly. Needing hints in an Atlassian DSA round is not automatically disqualifying, but it shifts the scoring from "strong pass" to "borderline," and borderline does not advance in a 6-round process.

3. Custom comparator complexity in Ruby. Ruby's Comparable module and <=> operator are different from Java's Comparator or Python's functools.cmp_to_key. Building a custom comparator class in Ruby under time pressure, with a changing problem statement, compounded the difficulty.

Result: Rejected. The candidate did not advance to Round 3.

Round 3: Snake Game LLD (45 minutes), conducted but did not count

Here is the unusual detail in this experience: the candidate was scheduled for Round 3 (LLD) in addition to Round 2, and both were conducted. The LLD round involved implementing a complete Snake game with test cases.

The Snake game is one of Atlassian's signature LLD problems. It appears across their India and Australia interview loops. The expected implementation covers: a grid/board, a snake (with growing body), food spawning, direction control, collision detection (wall and self), and a game loop. The test cases should cover: boundary wrapping or death, self-collision, food consumption, and score tracking.

The candidate completed the implementation but found the time constraint challenging. However, the LLD round result was moot: the rejection was based on Round 2 performance.

This is an important structural observation. Atlassian schedules multiple rounds simultaneously (or in rapid succession) and then evaluates holistically. But if Round 2 is a clear "no," the subsequent rounds do not override it. The LLD performance might have been strong, but the DSA rejection was decisive.

Rounds 4 through 6: Never reached

The full Atlassian Senior SWE loop includes 6 rounds:

Rounds 4, 5, and 6 are where Atlassian differentiates from pure-DSA companies. The Values round assesses alignment with Atlassian's core values (Open company, no BS; Build with heart and balance; Don't #@!% the customer; Play as a team; Be the change you seek). The Management round evaluates leadership and project ownership. These rounds are unique to Atlassian and cannot be prepared for with LeetCode.

But you cannot reach them without clearing Rounds 2 and 3.

The preparation gap

The candidate disclosed their preparation approach: 2 weeks before the Karat round, 30 to 40 data structure problems, mostly easy and medium difficulty. The candidate's self-assessment after rejection: this was insufficient.

Why 30 to 40 problems is not enough for Atlassian:

Atlassian's DSA rounds are calibrated at medium-to-hard difficulty with real-time requirement changes. A portfolio of 30 easy/medium problems does not build the pattern recognition needed for problems that evolve mid-round. The recommended preparation depth for Atlassian Senior SWE is:

• 100+ problems across 8+ categories (arrays, strings, trees, graphs, DP, heaps, stacks/queues, linked lists)
• At least 20 hard problems with follow-up variations
• Custom comparator problems specifically (Atlassian asks these frequently)
• Practice with changing requirements: have a study partner modify problem constraints mid-solve

The candidate also mentioned not researching Atlassian's previously asked questions. This matters because Atlassian recycles problem patterns (not exact problems, but structural patterns like ballot counting, ticket allocation, scheduling). Glassdoor and LeetCode discussion threads for Atlassian are useful pre-interview resources.

8 years of experience versus DSA: the mismatch

This experience illustrates a tension in product company hiring that affects senior engineers disproportionately. The candidate had 8 years of production software engineering at two companies. Staff-level title. Real systems built and maintained.

None of that mattered in Round 2.

Atlassian's interview process evaluates DSA, LLD, HLD, values, and management as separate axes. Being excellent at 4 of 5 does not compensate for failing 1 of 5. The DSA round is a binary gate: pass or fail. 8 years of production experience does not earn you a pass on a ballot-counting problem if you cannot implement the custom comparator in time.

This is not a criticism of the process. It is a statement of how the process works. Senior engineers targeting Atlassian (or any product company with a DSA gate) must dedicate the same preparation time to DSA as a fresher would, regardless of their production experience. The market does not provide a seniority exemption.

What Ruby users should know about Atlassian interviews

Ruby is a valid language choice for Atlassian's Coderbyte rounds, but it introduces friction:

1. Comparator syntax is different. Ruby's <=> (spaceship operator) and Comparable mixin work differently from Java's Comparator.compare() or Python's key functions. Practice custom sorting in Ruby specifically.

2. Test frameworks matter in LLD. The Snake game round requires test cases. If you use Ruby, know minitest or rspec syntax well enough to write assertions under time pressure.

3. Coderbyte's Ruby environment may not support all gems. Stick to stdlib.

4. Interviewers may not know Ruby. If your interviewer's primary language is Java or Python, they may struggle to read your Ruby code. Write explicit variable names and avoid Ruby-specific idioms (blocks, procs, method_missing) unless asked.

Verification note

PapersAdda's verification standard requires a publicly accessible post URL, per-round detail from the candidate, and a stated outcome. This post meets all three criteria. The candidate named the rounds, described the Karat format, identified the ballot-counting problem pattern, and documented the rejection.

Source: Atlassian Interview Experience by Gagandeep Singh on his personal blog.

Verification window: Published May 2024, describing events from November 2023. The Karat screening format, the Snake game LLD problem, and the 6-round structure are consistent with other Atlassian India interview reports from the same period.

Also on PapersAdda

• Google L4 India: 7-Round Downlevel to Rejection, when the process keeps extending and the outcome keeps worsening
• Goldman Sachs Engineering Analyst 2025: 10.5-Hour Campus Marathon, another multi-round endurance test, different outcome
• Uber SDE-1 India 2025: Google Sheets LLD Rejection, the LLD communication gap that decides outcomes
• Adobe MTS Off-Campus 2022: 4 Rounds in 1 Day, single-day interview loop, same pressure, different company

Quick disclosure: candidates report the patterns summarised above, and details differ by role and year. Cross-check the official notification and your own invite email for the version that actually applies to you before you prepare around any figure.