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IBM interview notes, page 3 of 4

Large Enterprises

Most of these IBM write-ups come from Software Engineers (32), then Data Scientists (6) and Product Managers (1). The most reported rounds are the technical phone screen (25), the online assessment (10), the hiring manager screen (1) and the behavioral / leadership round (1).

39 interview notes · updated Oct 2026

IBM·Software Engineer·Hiring Manager Screen

Jun 2026
Interviewed for a product analyst role at IBM. Just one question worth noting but it was the kind that sounds easy until you're actually in it.
  • How would you explain your analytical findings and the methods behind them to a non-technical audience?

“I rambled a bit about simplifying jargon and using visuals, which felt thin the moment I said it.”

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IBM·Software Engineer·Online Assessment (OA)

Jun 2026
IBM intern OA as a rising sophomore. Two coding questions, one doable and one absolutely brutal. The second question involved navigating a large existing codebase to fix bugs, which was a nightmare for someone with zero real dev experience.
  • Solve a standard algorithmic coding problem (LeetCode-style, moderate difficulty).
  • Given a large existing code repository, identify and fix bugs within the codebase.

“Passed all the test cases on this one so at least something went right.”

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IBM·Software Engineer·Technical Phone Screen

Jun 2026
IBM DevSecOps round that was pretty much a deep dive into Kubernetes troubleshooting. One question, lots of expected follow-up, felt more like a technical screen than a full panel.
  • A Kubernetes pod running a JDBC service is stuck in CrashLoopBackOff. Walk me through how you'd diagnose and fix it.

“This one has a lot of surface area and I think I handled the first layer fine (kubectl describe, checking events, exit codes) but fumbled a bit when they pushed on the JDBC-specific angle.”

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IBM·Software Engineer·Technical Phone Screen

Jun 2026
IBM DevSecOps round that leaned heavily on pipeline fundamentals. One big question that sprawled into like four sub-questions, which felt a bit overwhelming in the moment.
  • Walk me through CI/CD: what's the difference between continuous integration, continuous delivery, and continuous deployment, and how do typical pipeline stages fit together?
  • Which CI/CD tools have you actually used, and what did configuring pipelines look like in practice?
  • How do you handle a failed deployment in a pipeline, and what does your rollback process look like?

“I knew the definitions but fumbled the delivery vs deployment distinction under pressure.”

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IBM·Software Engineer·Onsite - System Design / Architecture

Jul 2026
IBM software engineer interview with a meaty systems question about multithreaded convolution. The kind of problem that sounds approachable until you're actually in the room trying to talk through SIMD, false sharing, and load balancing all at once.
  • Design and implement a multithreaded CPU-based valid 1D convolution. For three specific scenarios (short kernel, full-length kernel, and a thread-capped environment with up to 100 workers), explain how you'd partition work across threads, handle cache locality, avoid false sharing, manage synchronization, apply SIMD vectorization, and choose tile and chunk sizes. Provide pseudocode or an API-level design for a unified configurable routine.

“This one hit me harder than I expected.”

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IBM·Software Engineer·Technical Phone Screen

Jul 2026
IBM software engineer interview that was basically one big open-ended question about AI in the workplace. Not a coding round at all, more of a values and judgment call kind of conversation. Felt less like a technical screen and more like they wanted to know if you'd actually thought about this stuff.
  • What are your thoughts on using generative AI tools in a professional engineering context? Walk through where you'd use them, where you'd stay away, how you'd handle security and correctness concerns, and how you'd roll out guidelines to a team.

“This is a lot of ground for one question.”

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IBM·Software Engineer·Technical Phone Screen

Jul 2026
IBM DevSecOps round that felt more like a whiteboard philosophy session than a technical grilling. The containerization question took up most of the time and went deeper than I expected.
  • Why would you containerize an application? Walk through the motivations and benefits.

“I started with the obvious stuff, environment consistency across dev/test/prod, and the interviewer just nodded and waited.”

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IBM·Software Engineer·Technical Phone Screen

Jul 2026
IBM software engineer interview with a meaty scheduling algorithm problem that had a bunch of follow-ups tacked on. The core question was interesting but the extensions kept coming and I ran out of steam toward the end.
  • Given busy interval schedules for multiple employees (half-open intervals in minutes, potentially unsorted and overlapping within each employee), find all maximal time windows during which every employee is free. Intervals are within a single day (0 to 1440 minutes).
  • How would you handle schedules given as strings like '09:30-12:00' and deal with mixed time zones across employees?
  • How would you extend this solution to span multiple days, or to handle streaming updates where employee schedules change in real time?
  • What is the time and space complexity of your solution, and what data structures did you choose and why?

“I went straight to merging intervals per employee first, then took the complement to get each person's free time, then intersected across everyone.”

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IBM·Software Engineer·Technical Phone Screen

Jul 2026
IBM software engineer round, got a scheduling problem that I've seen floating around on leetcode for a while. Nothing too surprising but it's the kind of question where you can fumble the implementation even if you know the idea.
  • Given a list of meeting time intervals, each as a [start, end] pair, find the minimum number of conference rooms needed to accommodate all meetings simultaneously.

“Knew this one.”

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IBM·Software Engineer·Online Assessment (OA)

Jul 2026
Took the IBM entry-level SWE online assessment and it was two very different problems back to back. The first was a graph/dependency thing, manageable once you see the structure. The second dropped you into a real codebase with failing tests and told you to figure it out, which was a completely different experience and nearly ran out the clock.
  • Solve a graph or dependency-based algorithmic problem.
  • Given an existing backend repository and a technical spec, debug failing tests covering API filtering, pagination, and Redis caching including cache invalidation edge cases.

“Not too bad once I stopped overthinking the setup and just mapped out the relationships.”

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