The Atlassian software engineer interview is evolving quickly, especially for those who support AI-integrated platforms at scale. Atlassian’s engineering headcount grew by over 600 last quarter alone, driven by expansions in R&D and the rollout of intelligent agents like Rovo AI. These systems are transforming how software is planned, built, and maintained, requiring engineers who understand both infrastructure and machine learning pipelines. With projects like the SBOM platform, Model Context Protocol Server, and cloud migration tooling gaining momentum, candidates must demonstrate real-world problem-solving across distributed systems and analytics. This guide helps you prepare for the kinds of technical, cross-functional questions Atlassian asks—so you can walk in with clarity, confidence, and the context needed to crack the interview.
The Atlassian software engineer interview reflects the company’s commitment to building transparent, distributed teams that ship high-impact features with technical excellence. A typical day for an Atlassian software engineer involves stand-ups, writing backend services in Java or Kotlin, crafting intuitive UIs in React, and deploying through Bitbucket Pipelines.
Engineers collaborate asynchronously using Confluence and participate in peer reviews that reinforce Atlassian’s “Open company, no BS” culture. The “Team Anywhere” model supports flexibility, enabling focused development and empowered decision-making regardless of location. Whether building secure backends for Rovo Agents or optimizing CI workflows, engineers are expected to balance autonomy with ownership. Understanding these rhythms and values provides the foundation to tackle Atlassian software engineer interview questions with clarity and authenticity.
The Atlassian software engineer salary is among the most competitive in the industry, with total compensation reaching up to $508K in the US for senior roles. Engineers contribute to products that serve millions globally, from Jira to Confluence, while benefiting from a flexible, remote-first culture that 92% say improves their productivity. With growth fueled by AI-driven development and enterprise cloud migration, the role offers real technical challenges and long-term career opportunities. Whether you’re passionate about distributed systems or developer tools, this environment is designed to reward innovation and impact. Let’s explore the Atlassian coding interview questions you’ll need to master to land the role. But let’s look at the interview process first.
The Atlassian software engineer interview process typically follows a structured and candidate-friendly path designed to assess technical skills, architectural thinking, and cultural alignment. Here are the steps involved in the process:
You begin by applying through Atlassian’s careers site, which filters candidates based on alignment with the job description and tech stack. A standout application will emphasize experience with relevant tools like Java, Kotlin, React, AWS, or Kubernetes. It helps to highlight real-world impact, such as projects involving CI/CD, cloud infrastructure, or AI workflows, since Atlassian increasingly relies on data-driven systems. Submitting a résumé that clearly links your experience to the company’s focus areas—like cloud migration or developer tools—will improve your chances of moving forward. Make sure your application reflects both individual contributions and team outcomes.
This 30-minute conversation evaluates your motivation, career direction, and team fit. Expect questions like “Why Atlassian?” or “What kind of problems do you enjoy solving?” Recruiters share insight into the company’s culture and interview process while aligning your goals with team openings. You’ll also cover availability, location preferences under the Team Anywhere policy, and compensation bands. You are encouraged to ask clarifying questions and should avoid stating salary expectations first. This is also your chance to highlight previous cross-functional experience and remote collaboration, which aligns well with Atlassian’s distributed-first work model.
The Karat coding screen consists of a 60-minute virtual interview with an experienced third-party engineer trained on Atlassian’s evaluation rubric. You’ll complete two medium-difficulty algorithm problems and several debugging or small design prompts. Languages are flexible, so choose one you’re fluent in. The focus is not just correctness but how clean, testable, and efficient your code is. Interviewers assess how well you articulate your thought process, especially around trade-offs and performance. Strong candidates explain their reasoning, handle edge cases proactively, and use examples or test cases to validate their logic.
The virtual loop spans roughly four hours, split into two 60-minute coding interviews, one 60-minute system design interview, and a 45-minute values-based conversation. Coding questions extend beyond Karat and may include the implementation of data structures or solving real-world problems. The design round explores how you would architect systems like feature flags, rate limiters, or messaging platforms, emphasizing trade-offs, scalability, and monitoring. The values interview focuses on behavioral questions about teamwork, ownership, and customer obsession. Your alignment with principles like “Don’t #@!% the customer” or “Build with heart and balance” matters as much as your technical decisions.
After interviews conclude, each interviewer provides calibrated feedback and a P-level score reflecting scope and technical depth. A hiring committee—independent from your interviewers—reviews all feedback to determine the final level and offer. This helps ensure consistent hiring standards across teams and roles. You may receive a direct offer, be recommended for a different level, or be declined. Atlassian emphasizes transparency, and recruiters often share context on outcomes. A clear track record of problem-solving, architectural clarity, and value alignment generally leads to strong hiring signals.
Junior candidates (typically P30 to P40) are evaluated primarily on core problem-solving and foundational system design thinking. Their interviews focus on learning agility, clean code habits, and collaborative potential. Senior roles (P50 and above) introduce deeper architectural conversations and expect leadership behaviors. You’ll likely be asked about designing resilient microservices, managing trade-offs in distributed systems, and mentoring others. Some interviews also assess your ability to influence product direction or manage ambiguity across functions. For insights into the kinds of design topics covered, search “atlassian senior software engineer interview questions” to see real-world examples and frameworks.
The Atlassian software engineer interview questions span a wide range of topics to evaluate not just your technical capabilities, but also your ability to think systematically, communicate clearly, and align with Atlassian’s engineering culture.
These Atlassian coding interview questions evaluate your ability to write efficient, readable solutions using core data structures and algorithms, often reflecting the types of challenges faced in an Atlassian coding interview or assessments seen in Atlassian hackerrank questions like the popular paths to a goal hackerrank solution:
1. Format an array of words into lines of specified length
To justify an array of words into lines of a specified length, iterate through the words and group them into lines that fit within the max_width
. Distribute extra spaces evenly between words using a round-robin approach, and handle the last line separately to ensure proper formatting.
2. Find the missing number from an array spanning from 0 to n
To find the missing number in an array of integers spanning from 0 to n, you can use two approaches. The first approach involves iterating through the array and checking for the missing number using a set. The second approach uses a mathematical formula to calculate the expected sum of numbers from 0 to n and subtracts the sum of the given array to find the missing number. Both methods achieve (O(n)) complexity.
3. Select a random number from a stream with equal probability
To solve this, use reservoir sampling. For each new number in the stream, generate a random number between 0 and the current count minus one. If the random number equals the current count minus one, replace the previously selected number with the new number. This ensures every number has an equal probability of being selected.
4. Write a Python function to find the longest increasing subsequence in a list of integers.
To solve this, use dynamic programming. Create a dp
array where each element represents the length of the longest increasing subsequence ending at that index. Iterate through the list, updating dp
based on previous elements, and return the maximum value in dp
.
To solve this, use the RANK()
function to rank employees’ salaries within each department, partitioned by department_id
and ordered by salary in descending order. Then, join the ranked results with the departments
table to get department names, and filter for ranks less than or equal to 3. Finally, concatenate the first and last names of employees and sort the results by department name (ascending) and salary (descending).
These Atlassian system design interview questions focus on your architectural thinking, especially how you design for scale, reliability, and cost. Common scenarios range from Atlassian system design questions like task schedulers and queues to specific prompts, such as the Atlassian rate limiter interview:
6. Design a podcast search engine with transcript and metadata capabilities.
To design a podcast search engine, you would need to index both the transcript and metadata of podcasts. This involves creating a pipeline to process and store podcast data, enabling efficient search functionality. The system should support full-text search on transcripts and metadata, and may include features like keyword matching, relevance ranking, and filtering by metadata attributes such as episode duration or release date.
7. How would you design a database for a ride-sharing app?
To design a database for a ride-sharing app, start by identifying use cases like app backend and analytics. For the backend, prioritize query speed and immutability, using a NoSQL database for flexibility. For analytics, use a star schema with dimension and fact tables, and consider regionalization to optimize costs and query speeds.
8. Design a database schema for a blogging platform
To design a blogging platform schema, create tables for users, posts, comments, and tags. Define relationships such as a one-to-many relationship between authors and posts, and a one-to-one relationship between posts and engagement metrics. Apply constraints like primary keys for unique identification and foreign keys for relationships. Consider additional constraints like ensuring the author’s join date is before their first post date and using enums for predefined tag values.
9. How would you build an ETL pipeline to get Stripe payment data into the database?
To build an ETL pipeline for Stripe payment data, start by extracting data from Stripe’s API, ensuring proper authentication and handling of API rate limits. Transform the data by cleaning, normalizing, and structuring it to match the schema of your internal data warehouse. Finally, load the transformed data into the warehouse using batch or streaming methods, depending on the frequency of updates required. Automate the pipeline using tools like Apache Airflow or AWS Glue for scheduling and monitoring.
10. How would you build a database for a consumer file storage company like Dropbox?
To design a database for a file storage company like Dropbox, you need to account for storing various file types, tracking file updates, and maintaining a history of changes. A relational database can be used to store metadata (e.g., file name, type, size, and timestamps), while a distributed file system like Amazon S3 or HDFS can store the actual file content. Versioning can be implemented by associating each file with a unique version ID and maintaining a history table to track changes.
These Atlassian JAVA or Python interview questions target your depth in backend systems, concurrency patterns, API design, and JVM optimization, with an emphasis on practical coding in Java or Kotlin alongside a solid understanding of REST and cloud-native development:
11. Write a function to check if one string is a subsequence of another string.
To determine if one string is a subsequence of another, traverse both strings from left to right. Compare characters of the first string with the second string, moving forward in both strings when a match is found. If all characters of the first string are matched in order, it is a subsequence.
12. Devise a Python method to count the number of lines in a 100 GB log file.
To count the number of lines in a 100 GB log file, you can use Python’s with
statement to read the file line by line, incrementing a counter for each line. Alternatively, you can read the file in chunks using a buffer and count the newline characters (\n
) in each chunk, which is more memory-efficient for large files. Both methods avoid loading the entire file into memory.
To solve this, split the paragraph into words and use a dictionary to count the frequency of each word. Then, sort the dictionary by frequency in descending order and return the top N words with their frequencies. The run-time is (O(n\log n)), where (n) is the number of words in the paragraph, due to the sorting step.
These Atlassian front-end interview questions test your ability to build performant, accessible, and maintainable interfaces, often using React, and may touch on component design, state management, or optimizing rendering performance:
14. How do you implement a responsive layout using CSS Grid or Flexbox?
To implement a responsive layout, use CSS Grid or Flexbox to define flexible and adaptive structures. For CSS Grid, define grid-template-areas and use media queries to adjust the grid layout for different screen sizes. For Flexbox, use properties like flex-wrap
, justify-content
, and align-items
to create a layout that adapts to varying screen dimensions. Media queries can also be used with Flexbox to fine-tune the layout for specific breakpoints.
15. Describe the steps you take to improve web application performance.
To improve web application performance, start by identifying bottlenecks using tools like browser developer tools, performance monitoring tools, or server logs. Optimize front-end performance by minimizing HTTP requests, compressing assets, and leveraging caching. On the back-end, focus on optimizing database queries, reducing server response times, and scaling infrastructure as needed. Regularly test and monitor performance to ensure consistent improvements.
16. What is the Virtual DOM and how does React use it to optimize rendering?
The Virtual DOM is a lightweight, in-memory representation of the actual DOM. React uses it to optimize rendering by first updating the Virtual DOM and then calculating the minimal set of changes required to update the real DOM. This process, known as reconciliation, reduces the performance overhead of direct DOM manipulation, making updates faster and more efficient.
Drawing from the Atlassian interview experience, senior software engineer candidates often share, these behavioral questions assess how well you embody Atlassian’s values in real work situations—from owning decisions to advocating for customers under pressure:
17. How comfortable are you presenting your insights?
Atlassian engineers are often expected to share results across teams and influence product direction through clear, data-backed communication. Your answer should reflect how you translate technical findings into business impact, especially in collaborative tools like Confluence or Loom. Share a story where you presented insights to cross-functional stakeholders—perhaps during a sprint review or post-incident retrospective—to show how you make complex information understandable and actionable.
18. What are your three biggest strengths and weaknesses you have identified in yourself?
This is a chance to align your personal growth with Atlassian’s values, like Open company, no bullshit and Be the change you seek. Choose strengths that resonate with teamwork, ownership, or innovation. For weaknesses, mention areas you’ve worked to improve, such as delegating tasks more effectively or pushing back when overloaded. Atlassian looks for people who show humility and take initiative to improve, not just those who label weaknesses cleverly.
At Atlassian, exceeding expectations often means proactively solving pain points before they escalate. Choose an example where you took extra initiative—like improving CI/CD pipelines, unblocking a teammate, or optimizing a user workflow—and walk through your process using the STAR format. Tie your actions back to team outcomes or customer value, since impact is more important than heroics.
This question touches directly on Atlassian’s collaborative ethos. Focus on how you practiced openness, actively sought feedback, and reached alignment even if it meant changing direction. Atlassian values respectful debate and data-driven discussions, so share a story that shows your ability to stay objective, empathetic, and focused on the team’s success over ego.
21. How do you prioritize multiple deadlines?
As a software engineer at Atlassian, you’ll often juggle tech debt, feature development, and operational duties. Describe a clear prioritization method—perhaps using Jira, story points, or the Eisenhower Matrix—and explain how you coordinate with product managers and designers to balance competing demands. Emphasize your ability to re-evaluate in real time and communicate status transparently, which reflects Atlassian’s value of playing as a team.
The best way to approach the Atlassian interview is with structure and intention. Start by reviewing common Atlassian data structure interview questions—especially those involving trees, heaps, and graph traversal. These show up frequently in coding rounds and test your ability to reason through recursive logic and edge-case handling. Practice writing clean, well-documented solutions that prioritize clarity over cleverness. When preparing for the Atlassian system design interview, simulate real sessions under time pressure with AI Interviewer.
Sketch architectures like notification services or rate limiters, then walk through trade-offs around scale, fault tolerance, and consistency. Interviewers want to see how you balance practicality with performance. Communication is equally important. Use the STAR method to frame behavioral responses and come prepared with examples where you lived Atlassian values—particularly “Don’t #@!% the customer.” Highlight moments where you prioritized end-user experience, navigated team conflict, or drove change from within.
System design and values rounds reward those who ask thoughtful, clarifying questions, so they demonstrate curiosity and humility alongside technical fluency. Mock interviews can sharpen your timing and confidence. Pair with peers and use our platform to simulate coding and design mock challenges. The Atlassian process emphasizes not just what you build, but how you think, speak, and collaborate. By investing in both technical prep and cultural storytelling, you’ll position yourself as a well-rounded candidate ready to thrive in Atlassian’s engineering culture.
Average Base Salary
Average Total Compensation
For senior candidates going through the Atlassian software engineer interview process, the stakes and rewards are even higher. At the P50 level, total compensation in the U.S. averages $346,000, with top performers reaching $500,000+ at P60. Senior engineers typically earn significant equity, especially in leadership-track roles involving architecture, mentorship, and cross-team initiatives. The compensation curve steepens substantially between P4 and P6, and many promotions include RSU refresh grants or scope-adjusted bonuses. International packages are competitive as well, with India-based P60 engineers earning ₹17.6M on average, and Australia packages aligning closely with U.S. base salaries (adjusted for cost of living and currency).
You can explore real-life interview insights and experiences on the Interview Query Atlassian discussion forums. From walkthroughs of the Karat screen to deep dives into system design prompts, these threads provide helpful context from fellow candidates. Many Atlassian software engineer applicants share prep tips, project experiences, and recruiter interactions, offering a well-rounded view of what to expect and how to succeed.
After reviewing this comprehensive guide, you’re now equipped with a clear roadmap to tackle the Atlassian software engineer interview with confidence. From understanding salary expectations and mastering coding patterns to preparing for high-impact system design questions, this article helps you move from curiosity to offer. Want to see how others succeeded? Read Hanna Lee’s Success Story. Need a targeted prep plan? Follow this learning path for DSA. Curious about specific challenges? Dive into our curated list of Engineering interview questions. Every link is designed to move you closer to your goal—landing and thriving in a role that builds the future of software.