Quantiphi Interview Experience (OnCampus) - Framework Engineer Role
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Hi everyone! I’m Sarah Khan, and I’d like to share my interview experience with Quantiphi. After interviewing with companies like Oracle, Deloitte, and Capgemini, I identi...
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Hi everyone! I’m Sarah Khan, and I’d like to share my interview experience with Quantiphi . After interviewing with companies like Oracle, Deloitte, and Capgemini, I identified my weak areas, worked on them, and ultimately got selected for my dream role at Quantiphi! Quantiphi is a service-based, AI-first digital engineering company founded in 2013. They specialize in AI, data analytics, cloud services, and marketing analytics. The company partners with leading platforms like AWS, Nvidia, Azure, and GCP. Eligibility Criteria Academic Requirements: 70% and above in 10th, 12th, and graduation/post-grad (till date). Backlogs: No active or dead backlogs. Roles Offered Quantiphi visited our college to recruit for the following roles: ML Engineer Business Analyst (subdivided into Sales Engineer and Business Analyst). Framework Engineer (subdivided into Data Engineer, Software Development Engineer (SDE), and Platform Engineer).
Note: Roles were assigned based on scores in the Online Assessment (OA), which considered aptitude, DSA, technical MCQs, and resume evaluation. Initially, I received the ML Engineer role, but later opted for Framework Engineer as it better matched my skills and interests.
Round 1 Online Assessment (OA) The OA was conducted on Unstop and divided into three timed sections: Total Questions: 76 Duration: 1 hour 30 minutes Scoring: Based on accuracy, with speed as a tiebreaker. Sections: Aptitude & Verbal Ability: Standard questions, manageable difficulty. Technical MCQs: Topics included debugging, time complexity, data structures, and basic HTML. DSA Questions: Graph-based Problem: Similar to the CSES shortest routes problem (couldn’t solve due to time constraints). Binary Search Problem: Similar to Koko Eating Bananas (solved). Dynamic Programming Problem: Similar to House Robber (solved). Out of 52 shortlisted candidates, I moved to the
next round. Preparation Tips for
OA Use Striver’s A-Z DSA sheet for quick revision. Practice technical MCQs on GeeksforGeeks, Gate Smashers, or InterviewBit. Prepare for aptitude with CareerRide, IndiaBix, or PrepInsta.
Round 2 Technical Interview 1 The first technical interview was conducted virtually on Unstop after a Pre-Placement Talk (PPT) by Quantiphi. Questions Asked: Resume-based Questions: In-depth discussion on projects and technologies (React, AWS, GCP, etc.). Java Questions: Explained concepts like the wrapper class, OOP principles, and inheritance with real-life examples. Git & GitHub: Explained concepts like Git Stash, merge conflicts, Git logs, and branching. ReactJS Questions: Discussed render methods, hooks (useState, useEffect, useRef), and their practical usage. Cloud Services: Shared basic knowledge of AWS and GCP (e.g., S3 buckets, EC2 instances). Project Deployment: Discussed SDLC, wireframing with Figma, and unit testing. DSA Problem: Solved a question on the largest sum contiguous subarray using an O(n) approach. Tips for this Round: Know your resume inside out. Be prepared to explain projects and tech stacks with examples. Brush up on version control (Git) and cloud platforms.
Round 3 Technical Interview 2 The second technical round was conducted by a senior technical lead, who had also attended the PPT. Key Focus Areas: Projects and Teamwork: Explained experiences from the Smart India Hackathon, leadership roles, and task management. Relational vs. Non-Relational Databases: Discussed horizontal vs. vertical scaling, sharding, and practical applications. Errors and Troubleshooting: Shared challenges faced while learning new technologies like Appwrite and React Native. SQL Query: Solved a problem using COUNT and GROUP BY clauses. Cultural Fit Questions: Shared my preferences for roles, how I approach new challenges, and long-term goals. Tips for this Round: Be ready to discuss teamwork and leadership experiences in depth. Prepare to explain database concepts, technical troubleshooting, and your approach to learning new tools.
Round 4 HR + Cultural Fitness Round The HR round was more relaxed and focused on assessing my personality and cultural alignment. Questions Asked: Self-introduction (tailored to emphasize my passions and extracurriculars). Detailed discussions about my projects, achievements, and internship experiences. Preferences for location (Mumbai or Bangalore) and working beyond office hours. I also connected with the HR interviewer over our shared experience as NSS volunteers, which added a personal touch. Final Verdict After a long day of assessments and interviews, I was thrilled to be selected as one of the 8 candidates for the Framework Engineer role! 🎉 Key Takeaways: Believe in your preparation and always stay confident. Customize your answers to reflect your strengths and align with the company’s values. Feel free to connect with me if you have any questions or need guidance. Good luck!
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About Quantiphi Interview Reports
This question was reported by a candidate who interviewed at Quantiphi. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.
Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Quantiphi are the higher-signal extractions to take from this report.
For broader preparation context, the Quantiphi interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.
How To Practice This Type of Question
Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.
Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Quantiphi reports consistently are the ones worth investing in; one-off niche problems are not.
During Your Quantiphi Round
Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.
The single most predictive failure mode in Quantiphi reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.