Atlassian software engineer candidates report online assessments or Karat screens, coding and design interviews, and values-focused conversations. The exact format varies, but clear technical reasoning and adaptable solutions recur across reports.
$185K
Avg. Base Comp
$250K
Avg. Total Comp
2-7 rounds
Typical Rounds
3-10 weeks
Process Length
Atlassian Software Engineer candidates in the supplied accounts describe processes beginning with an online assessment or technical interview and progressing to implementation, design, or behavioral conversations. Prepare to produce a working solution and explain how you would improve it. Candidates reported easy-to-medium DSA questions involving arrays, heaps, binary search, and intervals. One account emphasized that solving the initial problem was not enough: the interviewer expected optimization, edge-case analysis, and a discussion of time complexity.
Practical engineering exercises also appeared. Candidates described implementing a MERN-stack project, fixing password functionality in a small backend website, and explaining why validation may be needed on both the frontend and backend. AI-assisted coding was allowed or encouraged in some of these exercises, but the supplied reports show that candidates still needed to understand the resulting code and answer follow-up questions. Practice explaining file ownership, code organization, validation, and the decisions made during implementation.
Design appeared in some longer processes. One successful candidate reported a low-level design exercise involving rate limiting and a separate system-design interview with an ambiguous prompt. Start by clarifying missing requirements, then make the data structures, interfaces, and tradeoffs explicit instead of silently filling in the gaps.
Behavioral or manager conversations covered experience, projects, collaboration, leadership, team fit, and Atlassian’s values. The completed reports range from a two-stage process to a longer sequence with assessment, technical, code-design, system-design, and values conversations. Scheduling and decision timing also varied, so use recruiter guidance to confirm the expected path.
Synthesized from 27 candidate reports by our editorial team.
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Real interview reports from people who went through the Atlassian process.
The main challenge for me was that the interview was built around a MERN-stack project, while most of my preparation had been focused on DSA rather than web development. I was given a project and a problem statement to implement. An AI assistant was available, which made it more manageable, and I was able to build what the prompt asked for. Afterward, the interviewer asked follow-up questions about the work, and that was where I struggled because I did not know the answers to several of them.
The interviewer was friendly, so the atmosphere itself was not intimidating, but I felt that my lack of confidence showed throughout the conversation. They also asked about my areas of interest. I was not selected to move to the second round. From friends, I learned that the next round is an HR interview with questions tied to Atlassian's published values. My biggest takeaway is not to rely only on DSA prep if the role includes a stack-specific implementation task: be ready to explain the decisions you make while building the project, and go in confident. I would also read Atlassian's values on its website before the HR round.
Prep tip from this candidate
Prepare to implement a MERN-stack project and explain your choices in the follow-up discussion. If you reach the HR round, review Atlassian's published values, since its questions may be drawn directly from them.
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Sourced from candidate reports and verified by our team.
Topics based on recent interview experiences.
Featured question at Atlassian
Select the 2nd highest salary in the engineering department
| Question | |
|---|---|
| Integer to Roman | |
| Dijkstra implementation | |
| Target Indices | |
| Target Value Search | |
| Concurrent LLM Serving | |
| Decreasing Subsequent Values | |
| Why Do You Want to Work With Us | |
| LRU Cache 1 | |
| Empty Neighborhoods | |
| Top Three Salaries | |
| Merge Sorted Lists | |
| Closest SAT Scores | |
| Subscription Overlap | |
| Monthly Customer Report | |
| Random SQL Sample | |
| Minimum Change | |
| Raining in Seattle | |
| String Shift | |
| Rolling Bank Transactions | |
| Customer Orders | |
| Top 3 Users | |
| Comments Histogram | |
| Find the First Non-Repeating Character in a String | |
| Prime to N | |
| Daily Retention Summary | |
| The Brackets Problem | |
| Upsell Transactions | |
| Find the Missing Number | |
| Scrambled Tickets |
Synthesized from candidate reports. Individual experiences may vary.
Many candidates reported an online assessment or Karat-style screen. The coding difficulty ranged from basic to medium or harder DSA questions, and some screens included compact system-design or estimation prompts. Practice explaining your approach and complexity while working under time pressure.
Reports include DSA interviews on graphs, dynamic programming, heaps, queues, intervals, and strings, as well as practical work such as a React interface, a MERN project, and backend debugging. Be ready to handle edge cases, improve an initial solution, and explain code-organization choices.
Candidates reported rate limiting, middleware routing, hierarchical storage, tagging across systems, and social-media design. Start by clarifying assumptions, then make APIs, data structures, and trade-offs explicit. Some interviewers added constraints after the first workable proposal.
Behavioral conversations commonly covered past projects, collaboration, feedback, conflict, motivation, leadership, and Atlassian values. Prepare specific stories that show your individual contribution and decisions, including how you worked through a difficult team situation.
