I went through a detailed technical interview that really tested both my conceptual and practical knowledge. The interview started with a standard introduction, then moved into a deep dive on a project I'd worked on. I found this part was crucial — the interviewer spent significant time understanding the technologies I'd used, my role, and the decisions I made. If you've built something yourself from scratch, this shouldn't feel overwhelming, but if you relied heavily on AI without truly understanding the implementation, it becomes noticeably harder.
Beyond the project discussion, the interview covered theoretical foundations like DBMS concepts, object-oriented programming principles, and how they apply to real systems. There was also an easy-level DSA question focused on arrays, which felt like a way to assess problem-solving approach rather than pure algorithmic complexity. What stood out was how the interviewer connected everything back to architecture and design — they weren't just asking isolated technical questions, but probing whether I understood the bigger picture of system design.
The overall difficulty was moderate to challenging depending on your background. If you're coming in with strong project experience and a solid grasp of fundamentals, you can handle it. The interview felt personalized to my skills, which was helpful but also meant the bar shifted based on what I claimed to know. I'd recommend going in with concrete project examples you can explain end-to-end, and be prepared to discuss not just what you built, but why you made certain technical choices.
Prep tip from this candidate
Deep dive into one or two projects you've genuinely built yourself, and be ready to explain the architecture, technology choices, and lessons learned — the interview weights project understanding heavily alongside DSA.
