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LinkedIn interview notes, page 30 of 32

Large Enterprises

Most of these LinkedIn write-ups come from Software Engineers (156), then Product Managers (66) and Data Scientists (37). The most reported rounds are the technical phone screen (169), the product sense round (62), the system design round (42) and the behavioral / leadership round (20).

316 interview notes · updated Oct 2026

LinkedIn·Software Engineer·Technical Phone Screen

Jul 2026
LinkedIn software engineer interview with two coding problems back to back. One was a classic sliding window, the other was a custom graph/logic puzzle that I didn't see coming at all.
  • Given two strings s and t, find the smallest substring of s that contains all characters of t, including duplicates.
  • You're given a hashmap where each key is an animal and the value is a list of animals that can't be on the same river bank as it. Determine whether the set of exclusion rules is conflict-free (i.e., no contradictions exist).

“Knew this was a sliding window problem pretty fast, which was a relief.”

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LinkedIn·Product Manager·Onsite - Product Sense / Strategy

Jul 2026
LinkedIn PM interview, one product strategy question about growing their subscription business. Pretty open-ended, no obvious right answer, which I found both freeing and kind of stressful.
  • What features would you build to grow LinkedIn Premium subscriptions?

“I went straight to job seekers because that felt like the obvious Premium audience, but halfway through I realized I was basically just describing features that already exist.”

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LinkedIn·Data Scientist·Technical Phone Screen

Jul 2026
LinkedIn data scientist interview focused almost entirely on a single product analytics case about diagnosing a drop in job applications. It was one of those sessions where you think you've covered everything and then the follow-up goes three layers deeper than you expected.
  • The number of completed job applications submitted per day on LinkedIn has dropped sharply. Walk through how you would systematically diagnose this, including the analyses you'd run, KPIs you'd track, visualizations you'd build, and data you'd request.
  • How would you separate a product regression from an external cause like seasonality, a macro labor market shift, or an SEO drop?
  • What segmentation cuts would you prioritize to localize where the drop is coming from?
  • What specific visualizations would you build to communicate your findings, and what data would you actually request to support them?

“This is the whole interview, basically.”

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LinkedIn·Product Manager·Recruiter / HR Screen

Jul 2026
Short LinkedIn PM screen, basically just one question about what kind of role I was looking for. Not much to report.
  • What does your ideal PM role look like?

“Pretty standard opener but I still fumbled it a bit.”

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LinkedIn·Software Engineer·Technical Phone Screen

Jul 2026
LinkedIn software engineering interview focused on graph algorithms, specifically topological sort on a task dependency DAG. The follow-up pushed into parallel scheduling with a worker pool, which is where things got interesting.
  • Given a set of tasks with upstream dependencies forming a DAG, return a valid execution order for all tasks. If a cycle exists, report the DAG as invalid.
  • Extend your solution to support parallel execution with a worker pool of size k, returning batches of tasks that can run simultaneously. Also discuss how you'd handle dynamic task insertion.

“Started with Kahn's algorithm because tracking in-degrees felt cleaner to explain out loud.”

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LinkedIn·Software Engineer·Technical Phone Screen

Jul 2026
LinkedIn software engineer interview that covered a mix of web fundamentals and accessibility. Nothing too wild but the questions required more depth than I expected for what felt like a standard technical screen.
  • What are the differences between GET, POST, and PUT in HTTP, and how do idempotency and safety factor into when you'd use each?
  • Walk me through different CSS styling approaches like inline styles, classes, BEM, and CSS Modules. When would you actually reach for each one?
  • What web accessibility practices do you consider essential, and how would you go about testing for them?

“I knew the surface-level answer but fumbled a bit when they pushed on idempotency.”

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LinkedIn·Software Engineer·Onsite - System Design / Architecture

Jul 2026
LinkedIn system design screen for a software engineer role. One question, but it had a lot of surface area and I don't think I covered everything they were looking for.
  • You're given a basic web architecture: client hits DNS, then a load balancer, then an app service, then a database. The app service also calls a third-party external API. Walk through the potential issues with this setup and propose concrete improvements around scalability, reliability, and observability.

“I jumped straight into database scaling and talked about read replicas for a while, which felt safe.”

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LinkedIn·Product Manager·Hiring Manager Screen

Jul 2026
Interviewed at LinkedIn for what seemed like a product or program management role. One question about stakeholder prioritization, not much else to go on.
  • How would you handle competing stakeholders when trying to prioritize projects?

“I fumbled this a bit.”

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LinkedIn·Software Engineer·Hiring Manager Screen

Jul 2026
Interviewed at LinkedIn, got asked a fairly standard culture-fit question about the kinds of people I like working with. Not much else to go on from what I remember.
  • What kind of people do you enjoy working with?

“I gave some answer about liking people who are direct and collaborative, which felt fine in the moment but sounded pretty generic in retrospect.”

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LinkedIn·Software Engineer·Technical Phone Screen

Jul 2026
LinkedIn SWE interview that went deep into data structure design, specifically a max stack problem that kept expanding in scope. They wanted two full implementations plus a discussion of edge cases and concurrency, which felt like a lot to cover in one session.
  • Design a stack that supports push, pop, top, peekMax, and popMax operations, where popMax removes and returns the most recently pushed maximum element. Implement two versions: one with amortized O(1) operations using auxiliary structures, and one with O(log n) popMax using a balanced tree or heap with linked nodes.
  • How do you handle duplicate maximum values in both implementations, and what edge cases exist for empty structure operations?
  • If this max stack were used in a high-throughput production system, what concurrency concerns would you address and how?

“This one sprawled.”

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