Intuit SWE-2 Onsite Interview Experience and Preparation Process

Candidate Profile: Software Development Engineer at a MAANG company (2.3 years of experience). Applied via LinkedIn referral.

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Round 0 Technical Phone Interview (90 minutes)** The session combin

Candidate Profile: Software Development Engineer at a MAANG company (2.3 years of experience). Applied via LinkedIn referral.

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Round 0 Technical Phone Interview (90 minutes)** The session combined Data Structures and Algorithms with high-level system design concepts. *

DSA Problem 1: Plus One (with variations). *

DSA Problem 2: Validate IP Address. *

System Design & AI: Discussed strategies to ensure zero downtime for APIs and reviewed models used in current trending AI applications.

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Round 1 Craft Demonstration (90 minutes)** The candidate presented a pre-prepared introduction deck before executing a live coding task within a provided repository. The tech stack included Python, Flask, and Docker for a localized LLM. *

Task: Implement a new API endpoint in the existing repository. *

Execution: The process involved discussing the design approach, writing the code, handling edge cases/exceptions, and verifying functionality via Postman. *

Optimization: The session concluded with a discussion on code efficiency improvements.

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Round 2 Assessor (60 minutes)** This round focused on database architecture and algorithmic problem-solving. *

Database Design: The interviewer requested schema extensions for the Round 1 project. The candidate defined entity relationships, discussed normalization, and wrote SQL commands. *

Graph Database: The candidate demonstrated how to transform the relational schema and joins into a Graph database node structure. *

Coding Problem: Edit Distance. *

Solution: The candidate implemented a Brute Force solution followed by an optimized Dynamic Programming approach using C++.

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Round 3 AI & Quality Assurance (30 minutes)** *

Testing: The discussion covered unit testing strategies (positive and negative cases), End-to-End (E2E) testing, and production monitoring metrics for the API built in Round 1. *

AI Concepts: The interviewer probed knowledge on Retrieval-Augmented Generation (RAG), system prompts, and the definition and impact of temperature in LLMs.

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Round 4 Hiring Manager (30 minutes)** This session focused on behavioral questions and fit. *

Topics: Review of the project presented in the introduction, strategies for managing work pressure, and the rationale behind seeking a new role.

Verdict: Selected