SDE-2 Interview Experience at CRED (Rejected) | Dec 2025
Recently, I interviewed for an SDE-2 role at CRED. Sharing my experience in detail—both to help others and to reflect on what I learned.
How It Started
I received a call from HR mentioning that they got my profile via Instahyre. After a brief discussion about my background, they scheduled the interview process.
Round 1: Initial Screening (Online)
Duration: ~30 minutes (ended in ~20 minutes)
This was more like a pseudo hiring-manager screening round.
Discussion topics:
• My current tech stack and how I use it in production
• How I use AI tools in day-to-day engineering work
• High-level discussion about my work experience
The round felt conversational and was primarily to assess fit and breadth, not depth.
Outcome:
Next day, HR confirmed that I was moving to the next round.
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Round 2: Design + LLD (Face-to-Face, Onsite at CRED Office)
Duration: ~2 hours
Focus: Low-Level Design + Problem Solving
This round was aligned with CRED’s AI-Native Design & Coding expectations .
Problem Statement
Design a Flight Booking System (similar to MakeMyTrip).
Expectations & Discussion Areas
I was expected to lead the entire design, starting from scratch:
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Requirements
• Functional & non-functional requirements
• Clear scoping and assumptions -
Low Level Design
• Core Domain & Entities
• Database schema design and relationships -
Flight Search
• One-way and round-trip
• Connecting flights with at most 1 stop
• Search performance considerations -
Booking Flow
• Seat locking and seat booking
• Price fluctuation handling (each seat has its own price)
• Booking segments and consistency -
Multi-Vendor Problem (How to handle ?)
• You are one booking platform
• Other platforms (e.g., MakeMyTrip, Goibibo) also sell the same seats (My Answer : This will handle at airline end. Airline will lock on platforms behalf. (Interviewer convinced.))
• How to prevent double booking across platforms -
High-Level Architecture
• Services
• Database
• Caching (Redis)
• Messaging (Kafka)
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Take-Home Assignment
After the round, the interviewer asked me to:
• Submit a clear design document
• Build a working prototype within 24 hours
• Ensure all mentioned components are connected (DB, Redis, Kafka, etc.)
AI usage was explicitly allowed.
I implemented the system using Docker and Docker Compose, wired all components together, and submitted the project within the deadline.
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**Round 3: Hiring Manager Round (Face-to-Face, Onsite CRED Office)
**
Duration: ~1 hours (Went till ~1.5 hours)
Panel: 2 interviewers
Part 1 (First ~1 hour): Project & Experience Deep Dive
• Detailed discussion on my submitted project
• Architecture choices
• Trade-offs
• Past work experience
This part went well and felt like a healthy technical discussion.
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Part 2 (Last ~30 minutes): System & Fundamentals Deep Dive
This is where things got difficult.
Questions That Exposed Gaps
1. I mentioned database indexing → deep dive into LSM Trees
• I couldn’t explain it clearly
2. I mentioned BigTable → asked about SSTables
• Again, no clear answer
3. AI fundamentals:
• “Have you read Attention Is All You Need?”
• What is attention and why it matters?
4. Learning approach:
• Do you read research papers from OpenAI, Anthropic, Google, etc.?
• How do you understand how AI systems work internally?
These questions were chained, each going deeper based on my previous answers and worked i have done.
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Feedback & Verdict
The interviewer asked me to rate my own interview out of 10.
I said 6/10.
At the end, the interviewer was transparent and shared negative feedback, mainly around:
• Shallow understanding of fundamentals
• Mentioning concepts without deep clarity
Final Result: ❌ Rejected
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Key Takeaway (Most Important)
Surface-level knowledge will kill you in senior interviews.
If you mention:
• LSM Trees → you must know how they work
• BigTable → you must understand SSTables
• Attention → you must know why it exists and how it works
Name-dropping concepts without depth backfires hard.
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What I Learned
• Senior interviews are not about what you’ve used, but how deeply you understand it
• If you’re learning something:
• Go end-to-end
• Read internals
• Understand trade-offs
This interview was a humbling but extremely valuable experience—and a strong reminder to go deep, not wide.


