Role: Not Specified (Technical Role)
College: Not Specified
Interview Date: September 2025 (Approximate, based on article date)
Interview Type: Not Specified (Likely Full-Time)
Result: Selected
Difficulty: Medium-Hard
Rounds: 2 rounds
Topics Asked: Projects, OOPs, JWT, Middleware, Virtual DOM, Machine Learning, API, C++, DSA, SQL, Operating Systems, Normalization, Agentic AI, RAG (Retrieval Augmented Generation), Java Backend concepts, HR/Behavioral, Extra-curriculars
Experience:
The candidate interviewed with CHUBB, with the process consisting of two rounds.
Round 1: L1 - Technical Interview (40 min)
This round was purely technical, focusing on projects, core concepts, and problem-solving skills.
Questions:
- Self-Introduction
- Detailed discussion on projects (complete tech stack, architecture, real-world application)
- Why did you choose React over Angular?
- Explain OOPs concepts with real-world examples. What is Polymorphism?
- JWT and Middleware — what they are and their use cases.
- Difference between Abstract class and Interface.
- Different Access Modifiers.
- What is the Virtual DOM?
- What is Machine Learning (ML)? Types of ML. What is a Confusion Matrix?
- What is an API and why do we use it?
- Use of the base keyword in C++.
- What is an MCP Server?
- DSA Question → Valid Sudoku (LeetCode link mentioned).
- Difference between Delete, Drop, and Truncate in SQL.
- Difference between WHERE and HAVING.
- SQL query to find the second highest rating.
- Logical questions on SQL manipulations.
- What is Context Switching in operating systems?
- Why OOPs is important?
- What is Normalization in databases and why it is used?
This round was a deep mix of coding, CS fundamentals, and project-based discussions.
Round 2: L2 — Technical + Managerial Interview (20 min)
This round focused on both technical and personality aspects.
Questions:
- Self-Introduction
- Detailed discussion on projects (more focused on problem-solving and scalability)
- Extra-curriculars and club activities — leadership and management roles undertaken.
- Discussion on Agentic AI and RAG (Retrieval Augmented Generation).
- Java Backend concepts and related questions.
- A couple of HR-style questions to test cultural fit and motivation.
The candidate was selected.