Gen AI Engineer applicants have rated the interview process at Deloitte with 2.6 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 20% positive. To compare, the company-average is 73% positive. This is according to Glassdoor user ratings.
Candidates applying for Gen AI Engineer roles take an average of 19 days to get hired, when considering 5 user submitted interviews for this role. To compare, the hiring process at Deloitte overall takes an average of 14 days.
Common stages of the interview process at Deloitte as a Gen AI Engineer according to 5 Glassdoor interviews include:
One on one interview: 43%
Skills test: 43%
Presentation: 14%
Here are the most commonly searched roles for interview reports -
First, he joined the interview very late, and then he started criticizing me for my resume formatting.
I felt like he might have been envious.
He asked about my hometown, but throughout the interview, he was constantly checking his phone.
It seemed like he was not genuinely interested in taking my interview.
Interview questions [1]
Question 1
HomeTown , Current CTC(in tech round at the starting of an Interview),
Metrics , BLEU Score and ROGUE
It seems like he just knows this only
I explained RAGAS , he told no I want to know only about BLEU Score
I applied online. The process took 2 months. I interviewed at Deloitte (Washington, DC) in Apr 2024
Interview
First recruiter phone call to give and get details for the interview.
First round is an assignment that has ML concepts in a python notebook and create presentation slides
Then 3 rounds back to back 30mins each.
2 Technical Knowledge + Resume rounds
1 Behavior round
I applied through a recruiter. The process took 4 weeks. I interviewed at Deloitte (Bengaluru) in Jun 2025
Interview
i only had one round with Tech interview and it was rescheduled after i joined first time and got interviewed second time it was good total 1hr of interview
i was asked two basic python coding question
and discussed about 45 mins on Gen Ai
Interview questions [1]
Question 1
like how RAG, Agent LLM model works, RAG vs Agent, Shared memory between Agent. Scenior based question to how i will design agent, embedding models, how to access a very big RAG, stuffs like that