LinkedIn Software Engineer candidates describe a recruiter screen or online assessment, technical phone screens, and a final loop with coding, a design discussion and a hiring manager round. Medium LeetCode problems with follow-ups are the common thread.
$190K
Avg. Base Comp
$256K
Avg. Total Comp
Not reported
Typical Rounds
Not reported
Process Length
Candidates describe LinkedIn's Software Engineer interview as LeetCode-style coding with follow-ups, paired with a hiring manager conversation about your own projects. The path varies. Some candidates report an online assessment with two coding questions, a short recruiter call and a virtual loop of one technical and one behavioral round with the hiring manager. Others describe a recruiter call and a technical phone screen followed by a longer final loop. One candidate's final round packed in four DSA questions, a system design section and a conversation with the hiring managers.
The coding is mostly medium difficulty, with harder questions appearing in some loops. One candidate had two coding rounds with one medium and one hard question each. Reported problems include a tree question, a weighted random pick, a basic dynamic programming problem and an exercise converting any integer up to 100,000,000 into English words. Interviewers reportedly care about how you reason, so narrate your approach, run test cases out loud and state time and space complexity. Follow-ups are common, such as a binary search extension on the weighted random pick and a concurrency twist on a string manipulation problem.
System design is the least predictable round. One candidate was told to keep it verbal with no visual aids and found the prompt poorly defined. Another described a design round on well-known topics, and a third was asked to explain CAP theorem with a real-world example. One candidate also described a long round debugging a 200 to 300 line code sample with AI involved. They had to adjust it to produce a different output and then explain the approach verbally.
Prepare detailed stories for the hiring manager round, including the trade-offs in projects you built and why you want LinkedIn. Outcomes are mixed. Some candidates heard back with an offer within days. Another chased the recruiter repeatedly, never received feedback and did not get an offer.
Synthesized from 31 candidate reports by our editorial team.
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Real interview reports from people who went through the Linkedin process.
The system design round was the only part of my LinkedIn onsite where I felt I needed help. I was interviewing at the Staff Software Engineer level in the US, and the loop included coding, an AI coding round, craftsmanship, a host/leader conversation, and system design, following a phone screen. The phone screen came first, and I advanced to the onsite after passing it.
The regular coding round was a variation on a LinkedIn-tagged LeetCode-style problem rather than an exact repeat. The AI coding round was a newer addition and was less intimidating than I expected: I described at a high level how I would solve the problem and use AI as part of the workflow. The important part was not blindly accepting an answer. I was asked why I would accept the AI-generated solution, so I had to defend it and demonstrate that I was still in control of the reasoning.
I felt strong about phone screen, coding, and AI coding. Craftsmanship and the host/leader round were harder for me to self-evaluate; the host manager conversation focused on past experience and did not feel like a standard behavioral round. In system design, I needed one hint before I got to the core data structure, largely because I blanked on its name. My overall impression is that LinkedIn is very selective, especially for system design, so I would not over-read your own perception of how each round went. The outcome was not shared. For prep, practice variations of LinkedIn-tagged coding and system-design questions, and rehearse explaining why you would trust, reject, or revise an AI-proposed solution rather than simply using it.
Prep tip from this candidate
Prepare to explain and defend AI-assisted solutions: articulate your own approach first, then justify why an AI suggestion is correct or how you would revise it. Also expect variations of LinkedIn-tagged coding and system-design questions rather than exact repeats.
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Sourced from candidate reports and verified by our team.
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 | |
|---|---|
| Over-Budget Projects | |
| Raining in Seattle | |
| Job Recommendation | |
| User Experience Percentage | |
| Bagging vs Boosting | |
| Integer to Roman | |
| Month Over Month | |
| Delivery Estimate Model | |
| The Brackets Problem | |
| Repeat Job Postings | |
| Nearest Common Ancestor | |
| String Mapping | |
| Find Duplicate Numbers in a List | |
| Reservoir Sampling Stream | |
| Target Indices | |
| Hurdles In Data Projects | |
| Biased Random Number Generator | |
| Real-Time Hashtag Partitioning | |
| Merge N Sorted Lists | |
| Multi-Reaction | |
| Target Value Search | |
| Type I and II Errors | |
| Same Characters | |
| Possible Triangles | |
| Max Width | |
| Binary Tree Validation | |
| Combinational Dice Rolls | |
| Scrapers or Users | |
| Optimistic vs Pessimistic Locking |
Synthesized from candidate reports. Individual experiences may vary.
Starts vary. Some candidates began with an online assessment of two coding questions followed by a short recruiter call. Others started with a recruiter conversation about the role and their background. One candidate received an email afterward laying out the interview loop with preparation hints. Another, who was not selected, said they had to chase the recruiter several times and never received feedback.
Reported screens included a medium string manipulation problem with a concurrency follow-up. Another was a weighted random pick problem where the interviewer pushed toward binary search. One candidate's phone screen spent much of the time on current and past projects before a medium coding question at the end. Another candidate's first technical screen was a single DSA question.
Final loops included one or more coding rounds. One candidate had two coding rounds with two questions each, one medium and one hard. Another faced four DSA questions within a single final round. Others reported a medium tree question, a basic dynamic programming problem and a careful implementation task to write out any integer up to 100,000,000 in English. One candidate also debugged a 200 to 300 line code sample with AI involved.
One candidate was asked to keep the design discussion verbal with no visual aids. They felt the question was unclear and shifted as they asked for clarification. Another described a verbal design discussion rather than a whiteboard exercise. A third was asked to explain CAP theorem with a real-world example alongside backend fundamentals. Another reported a design round on well-known system design topics.
Candidates describe a hiring manager conversation centered on past projects, including the pros and cons of what they built, plus tell-me-about-yourself and why LinkedIn. One candidate discussed software craftsmanship, leadership and execution and walked through a technical project. Another was asked about a time they solved something big or handled a challenging project. One candidate said the hiring managers responded well to discussion of trade-offs and values.
