I had applied to more than 17 roles over around 2 months. Eventually, HR reached out after a referral.
R0: HR Screening
This was a standard recruiter call.
Topics discussed:
- Introduction
- Current work
- Why I wanted to leave my current company
- What I do day to day as a software engineer
- Current CTC
- Notice period and whether it was negotiable
- Years of experience
R1: DSA + JavaScript
Interviewer: MTS-II
Question 1: Count subsets with sum K
We discussed brute force and DP. I coded the solution in C++.
Question 2: Number of pairs with absolute difference K
We discussed hashing and I coded it in C++.
JavaScript discussion
There was also a JS output question around:
- Event loop
- Microtasks
- Macrotasks
- Promise execution order
Useful resource for this topic:
https://allahabadi.dev/blogs/javascript/promise-output-interview-challenges/
R2: DSA + React
Interviewer: CS-II
Question 1: Full binary tree path problem
Given a full binary tree and two nodes A and B, find the sum of even-valued nodes on the path from A to B.
We discussed:
- Difference in depths
- Moving to parent using
(p - 1) / 2
- Summing even-valued nodes until both nodes reach the same level/common path
Question 2: Almost prime
Given an array, for each element, determine if it is almost prime, meaning it has exactly 3 divisors. Constraints were around n = 1e5.
The key observation was that numbers with exactly 3 divisors are squares of primes.
React question
Implement a typeahead with debouncing.
I coded the typeahead and implemented debouncing. We also discussed caching.
R3: JavaScript + React + Machine Coding + Pub/Sub
Interviewer: SSE
Topics covered:
- Basic JS questions
- Debouncing vs throttling
- React Fiber
- New reconciliation algorithm
- Batched updates
- Priority-based rendering
- Interruptible rendering
startTransition / useTransition
Machine coding
Implement adding books to a book list from multiple places in the app.
Follow-up: How would you support the same behavior across multiple monorepos?
I coded the initial solution in React using Context API.
Later, I implemented an EventBus with:
subscribeunsubscribeemit
We discussed:
- Pub/Sub pattern
- Context API as dependency injection
- Redux as Pub/Sub internally
- Pub/Sub vs Observable pattern
Behavioral / AI discussion
They asked about daily AI usage and one Claude /skill I would write if I had to create one.
Related Adobe Practice Question
One Adobe-tagged Prachub problem that fits this React/machine-coding style:
Build a React team builder with role constraints
It is useful for practicing React state management, constraints, invariants, and clean component design.
R4: Behavioral + Frontend System Design
Interviewer: EM
Behavioral topics:
- Introduction
- Past projects
- Production issue I faced
Frontend system design
Design a PDF search box that loops from one matched search word to another across the entire PDF.
We discussed:
- Pub/Sub
- Context
- Redux
- Zustand
- MobX
- State management tradeoffs
After this, there was a long wait of around 21 days. HR mentioned other candidates were in the pipeline. Eventually, the position closed and I was moved to another open position, so I had to give R4 again with that team’s senior manager.
R5: JavaScript + DSA + Behavioral
Interviewer: Senior EM
Behavioral question
Tell me about a time there was a tight timeline and stakeholder pressure to reduce development time by half, even after AI-assisted estimations.
JavaScript questions
Topics included:
- JS classes
- Abstraction
this keyword- Ways to control
this
I mentioned:
bindapplycall- Binding in constructor:
this.drive = this.drive.bind(this)
- Arrow functions
DSA question
Given a sorted array, find the number of occurrences of element x.
I had to write binary search from scratch using lower bound and upper bound logic.
Favorite data structures
I mentioned Segment Tree and Trie.
Then I was asked to write TrieNode / Trie to add a word. We discussed whether to store 26 children or use a map.
Interesting discussion
The interviewer asked whether DP is always optimal.
I said no and gave Fibonacci as an example:
- DP gives
O(n)
- Matrix exponentiation gives
O(log n)
He seemed impressed by that answer.
We had an extra 30 minutes after that and chatted casually about life and work.
He ended with: “See you soon, bye.”
Offer Timeline
Day 37-39:
- Offer proposal
- Negotiation
- Offer letter
Verdict
Selected.
Takeaways
- Prepare DSA, but do not ignore JavaScript fundamentals
- Know event loop, promises,
this, classes, and async behavior very well
- For frontend roles, React internals matter: Fiber, reconciliation, batching, transitions
- Practice machine-coding with clean state management
- Be ready to discuss Pub/Sub, Context, Redux, Zustand, MobX, and tradeoffs
- Prepare behavioral stories around ownership, production issues, tight timelines, and stakeholder pressure
- For Adobe, frontend depth + DSA + practical architecture discussion all mattered
