LinkedIn Software Engineer interview typically runs 3–5 rounds: recruiter screen, technical phone screen, and onsite rounds covering DSA, system design, and a hiring manager behavioral. The process takes a few weeks and is distinguished by its strong emphasis on verbal reasoning and explaining logic alongside coding.
$119K
Avg. Base Comp
$300K
Avg. Total Comp
4-6
Typical Rounds
3-5 weeks
Process Length
We've coached a lot of candidates through LinkedIn's software engineering process, and the pattern that stands out most is the gap between what the prep material promises and what actually happens in the room. Multiple candidates reported preparing for a polished whiteboard-style system design round based on LinkedIn's own guidance, only to be told mid-interview to put away visual aids and keep it verbal — with one candidate describing a prompt that drifted into OS development territory with shifting goalposts. That disconnect has tripped up otherwise strong candidates who were well-prepared on paper.
On the coding side, the questions themselves are rarely exotic — Valid Palindrome, maximum subarray, lowest common ancestor, binary search variants — but the expectation is that you extend your solution, not just reach it. A recurring theme across accepted-offer candidates is that interviewers layered follow-ups that changed the shape of the problem: a string manipulation question that added concurrency, a weighted random-pick problem pushed toward binary search, a medium tree question followed by a harder variant. Candidates who got offers consistently mentioned talking through test cases and complexity out loud as something that visibly landed well with interviewers.
The other non-obvious factor is how much weight LinkedIn puts on your project history. This isn't just a resume check — multiple rounds across different interview paths opened with deep dives into past work, asking candidates to defend trade-offs and explain decisions. The hiring manager conversation in particular tends to be a long, probing discussion about what you built and why, not a soft landing after the hard technical rounds. Candidates who treated that conversation as low-stakes often found it was anything but.
Synthetized from 11 candidates reports by our editorial team.
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Real interview reports from people who went through the Linkedin process.
I got pretty lucky in the coding round because the main problem was maximum subarray sum, and I had actually seen that exact question on prachub.com a few days before. The process started with a recruiter screen, then moved into a technical phone interview that was very focused on algorithms and data structures, and I also had to answer a few behavioral questions about my background and experience. After that there was a final onsite round. The whole thing felt pretty intense, but the structure itself was straightforward once I knew what each stage was testing.
The other technical screen I went through was live coding on HackerRank, but the interviewer explicitly cared more about explaining the logic than running the code. That round was based on Valid Palindrome, which was easy-level, and there was a follow-up question built off the same idea. The interviewer was friendly and tried to keep the atmosphere comfortable, which helped a lot. Overall, the process was more about clean communication and solid fundamentals than anything exotic. I ended up receiving an offer and accepted it, so I’d say the biggest takeaway is to be ready for classic algorithm questions, talk through your reasoning clearly, and not assume you need to brute-force the coding screen with execution.
Prep tip from this candidate
Be ready for classic array/string problems like maximum subarray sum and Valid Palindrome, and practice explaining your approach clearly without relying on running the code. Also expect at least one behavioral section alongside the technical screens.
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Topics based on recent interview experiences.
Featured question at Linkedin
Given two sorted lists, write a function to merge them into one sorted list.
| Question | |
|---|---|
| Raining in Seattle | |
| User Experience Percentage | |
| Delivery Estimate Model | |
| Month Over Month | |
| Integer to Roman | |
| The Brackets Problem | |
| Over-Budget Projects | |
| Repeat Job Postings | |
| Nearest Common Ancestor | |
| String Mapping | |
| Find Duplicate Numbers in a List | |
| Reservoir Sampling Stream | |
| Hurdles In Data Projects | |
| Target Indices | |
| Real-Time Hashtag Partitioning | |
| Type I and II Errors | |
| Target Value Search | |
| Merge N Sorted Lists | |
| Same Characters | |
| Possible Triangles | |
| Binary Tree Validation | |
| Max Width | |
| Combinational Dice Rolls | |
| Scrapers or Users | |
| Optimistic vs Pessimistic Locking | |
| Optimal Host | |
| 180 Day Job Postings | |
| Shortest Path Algorithms | |
| k-Means from Scratch |
Synthesized from candidate reports. Individual experiences may vary.
An initial call with a recruiter covering basic behavioral questions, your background, and an overview of the role. Recruiters are generally responsive and may provide hints on how to prepare for subsequent rounds.
A take-home or asynchronous coding assessment consisting of two LeetCode-style coding questions, typically ranging from easy to medium difficulty. Not all candidates receive this step; it appears more commonly in certain hiring pipelines.
A live coding interview conducted on HackerRank where the interviewer emphasizes explaining your logic clearly over simply running the code. Expect one to two LeetCode-style problems (easy to medium) covering topics like strings, arrays, binary search, or trees, along with brief behavioral or resume-based questions.
A series of back-to-back rounds that typically includes two to three DSA coding rounds (medium to hard LeetCode-style problems, often featuring BFS/DFS, trees, dynamic programming, and binary search), one system design round (discussed verbally rather than on a whiteboard), and one hiring manager behavioral round focused on past projects, trade-offs, and motivation for joining LinkedIn.
A conversational round with the hiring manager covering behavioral questions such as 'why LinkedIn,' a deep dive into your resume and past projects including pros and cons of decisions made, and discussion of engineering values and trade-offs. This round is generally described as laid-back in tone but substantive in content.