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Summary
I had a phone interview for a Senior Frontend Engineer role at Intuit. I successfully solved the coding and OOP problems, but unexpected questions on AI/ML impacted the outcome, leading to a likely no-hire.
Full Experience
Background - Currently working as frontend engineer in India's leading quick-commerce company.
TPI Phone Interview [1.5 hours scheduled, lasted ~45 minutes]
Introduction (5 mins)
Brief self-introduction and discussion around my current projects and responsibilities.
JavaScript Question
Problem:
Write two functions:
A() returns 2 after 2 seconds
B() returns 3 after 3 seconds
Return their sum in two ways:
Parallel execution → Total time: 3 seconds
Sequential execution → Total time: 5 seconds
Solution - used promise.all and normal async await handling, solved in 10 minutes
OOP Question - Classes
Problem:
Create Student and Teacher classes with some shared and some unique properties.
Required functionalities:
getTotalStrength()
getStudentInfo()
getTeacherSubjects()
And a few more operations.
Solution - created a base class SchoolMember, from that extends student and teacher and so on, solved in 15 minutes
Machine coding
Next question was pretty easy, normal todo list to add, delete, mark as complete, search , solved in 10 minutes
Then he ask me about GenAI, RAG, LLM, Finetuning, and more questions related to AI and ML
Wasn’t expecting this as the job description didn’t mention anything AI/ML-related, and I primarily work as a frontend engineer
Answered what I could, but got stuck in some areas due to limited exposure
The interview went well overall — I solved all the coding and design problems efficiently. However, the unexpected AI/ML questions toward the end likely impacted the outcome. It's been over 3 days with no update, so assuming it's a no-hire.
Interview Questions (4)
Write two functions:
A() returns 2 after 2 seconds
B() returns 3 after 3 seconds
Return their sum in two ways:
Parallel execution → Total time: 3 seconds
Sequential execution → Total time: 5 seconds
Create Student and Teacher classes with some shared and some unique properties.
Required functionalities:
getTotalStrength()
getStudentInfo()
getTeacherSubjects()
And a few more operations.
Implement a todo list application with functionalities to add, delete, mark as complete, and search for tasks.
Questions about GenAI, RAG, LLM, Finetuning, and other AI/ML-related topics.