← Back to Directory

Atlassian interview notes, page 5 of 11

Large Enterprises

Most of these Atlassian write-ups come from Software Engineers (60), then Machine Learning Engineers (28) and Data Scientists (12). The most reported rounds are the technical phone screen (45), the system design round (38), the behavioral / leadership round (10) and the onsite coding round (3).

104 interview notes · updated Aug 2026

Atlassian·Machine Learning Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Atlassian for an ML Engineer role. They pick apart your projects in real detail, not just the high-level story but specifically what you personally decided and why.
  • Walk me through a project you owned. What specific decisions did you make, and what was your individual contribution versus the team's?
  • What did you actually learn from that project, and how has it changed the way you work?

“The part that tripped me up was how persistent they were.”

View Post

Atlassian·Data Scientist·Technical Phone Screen

May 2026
Atlassian data scientist interview with a pretty gnarly algorithmic problem that felt more like a competitive programming round than anything I expected for this role. The problem was well-defined but the solution space was wider than it looked at first glance.
  • Given an array of n integers and an integer k, place k cluster centers to minimize the maximum L1 distance from any point to its nearest center. Return that minimum possible distance.

“I sorted the array first which was the right instinct, but then I fumbled around trying to brute force placements before realizing binary search on the answer was the cleaner path.”

View Post

Atlassian·Machine Learning Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round at Atlassian for an ML Engineer role. Just one question but they really sat with it, the follow-up probing went longer than I expected.
  • Describe a situation where you disagreed with a decision made by a manager, peer, or stakeholder. What was the context, how did you handle raising your concerns, and what happened as a result?

“I had a decent story ready about a modeling approach I pushed back on, but the follow-ups got granular fast.”

View Post

Atlassian·Machine Learning Engineer·Onsite - Behavioral / Leadership

May 2026
Behavioral round for an MLE role at Atlassian, just the one question but it had a lot of layers to it. Left feeling like I gave a decent answer but probably undersold the stakeholder communication piece.
  • Describe a situation where you had to move forward despite significant ambiguity, such as unclear requirements, shifting priorities, or missing data. How did you frame the problem, what trade-offs did you accept, and how did you keep stakeholders informed about what you didn't know?

“I had a decent story ready but I spent too long on the problem setup and rushed the trade-offs section, which was probably what they actually cared about.”

View Post

Atlassian·Software Engineer·Onsite - System Design / Architecture

May 2026
Atlassian system design round, one big question that sprawled into a lot of sub-topics. The scope was broader than I expected and I felt like I was playing catch-up the whole time.
  • Design an authorization system that supports both role-based access control and resource-level permissions, covering the data model, permission evaluation logic, caching, and scaling to billions of checks per day.

“I started with the data model which felt safe, users, roles, permissions, resources, the join tables.”

View Post

Atlassian·Software Engineer·Onsite - System Design / Architecture

May 2026
Atlassian system design round focused entirely on a tree/hierarchy storage service. Pretty deep dive into API design, schema choices, and edge cases. Felt like they really wanted to see how you reason through tradeoffs rather than just recite textbook answers.
  • Design a service that stores a hierarchical tree of nodes and exposes REST APIs. You need to support adding a node under a parent and retrieving all descendants of a given node recursively.
  • Walk through your REST API design for this service. What endpoints would you expose, and what would the request and response shapes look like?
  • How would you prevent cycles from being introduced into the tree when adding new nodes?

“I jumped straight to adjacency list because it's the first thing that comes to mind, and the interviewer let me run with it for a bit before asking how I'd handle fetching all descendants efficiently.”

View Post

Atlassian·Software Engineer·Technical Phone Screen

May 2026
Atlassian technical phone screen that built on a previous org-tree problem, this time with employees belonging to multiple organizations. The twist made it a lot harder than I expected.
  • You have the org-tree LCA problem, but now an employee can belong to multiple organizations at once. Given two employees, find the deepest organization that contains both of them. Walk through how you'd change the data structure, compute ancestor sets for each employee, and find the deepest common ancestor. What are the time and space complexity tradeoffs?

“I'd done a version of LCA before so I thought I was fine.”

View Post

Atlassian·Data Scientist·Technical Phone Screen

May 2026
Atlassian Data Scientist interview with a coding-heavy system design problem. The question was more engineering-flavored than I expected for a DS role, which threw me off a bit.
  • Implement a function that takes a list of URLs (one per second) and returns '200' or '429' for each, enforcing two rate limits per address: no more than 5 requests in any 30-second window, and no more than 2 in any 5-second window.

“I knew sliding window conceptually but freezing up on the dual-window constraint cost me time.”

View Post

Atlassian·Software Engineer·Onsite - System Design / Architecture

May 2026
System design round at Atlassian for a software engineer role, focused entirely on building a cloud document storage service with deduplication. Pretty deep dive, lots of follow-ups on things I hadn't fully thought through beforehand.
  • Design a cloud document storage service that deduplicates identical and near-identical documents at scale.
  • How would you handle hash collisions and verify that two chunks with the same hash are actually identical?
  • Walk me through the storage layout for a chunk-based dedup system, specifically the chunk store and manifest structure.
  • How does encryption at rest interact with deduplication, and what is convergent encryption?
  • How would you implement garbage collection for orphaned chunks that are no longer referenced by any manifest?
  • How would you measure the deduplication ratio across your storage system, and what metrics matter?
  • Compare full-file hashing versus chunk-level deduplication for a workload of typical office documents.
  • How would you scale the metadata service that tracks chunk manifests and user file mappings?

“I started with full-file SHA-256 hashing and the interviewer immediately pushed back on what happens when two files differ by one line.”

View Post

Atlassian·Product Manager·Onsite - Product Sense / Strategy

May 2026
PM case interview at Atlassian, product sense round focused on a struggling onboarding scenario. One meaty question that took up most of the time.
  • New user return rates for a project management tool are low. How would you diagnose the problem and improve metrics like return rate, sign-up volume, and daily active usage within the first 15 days?

“This is the kind of question where I spent too long on diagnosis and ran out of time before getting to concrete solutions.”

View Post