Gupshup

All AI roles · updated 2026.07

Limited public evidence

“Included as a consequential modern Indian conversational ai employer with relevant product, engineering, data or AI roles.”

stages

2–5 weeks

end to end

practice questions

Hiring now

AI engineer roles are open right now

landed applies to roles like these for you, on each company’s own site, with answers written for the role.

Get 5x interviews10 free auto-applies. No card.

AI Engineer
InMobi · San Mateo, CA
Staff AI Engineer
Coupang · Seattle, USA
AI/ML Engineer
Kaizen Labs · New York, NY

Or practice this loop first

The interview, stage by stage

1
Founder or hiring manager screen60 min
speech and language qualityagent reliability
Prepare one quantified example demonstrating speech and language quality.
2
Practical role exercise60 min
agent reliabilitylatency
Prepare one quantified example demonstrating agent reliability.
3
Technical/product deep dive60 min
latencyenterprise integrations
Prepare one quantified example demonstrating latency.
4
Team values and ownership round90 min
enterprise integrationsevaluation
Prepare one quantified example demonstrating enterprise integrations.

What decides the offer

Speech and language quality

25%

Shows specific decisions and measurable evidence for speech and language quality.

Agent reliability

20%

Shows specific decisions and measurable evidence for agent reliability.

Latency

20%

Shows specific decisions and measurable evidence for latency.

Enterprise integrations

20%

Shows specific decisions and measurable evidence for enterprise integrations.

Evaluation

15%

Shows specific decisions and measurable evidence for evaluation.

They look hardest for speech and language quality, agent reliability, latency, enterprise integrations.

Your four weeks

Days 1–2

Company and market

·Map products, users, revenue model and competitors
·Write a one-page company thesis

Days 3–5

Core role skills

·Practice speech and language quality
·Practice agent reliability
·Practice latency

Days 6–8

Company-context cases

·Design a multilingual voice agent for Indian users.
·Evaluate code-switching and accent robustness.
·Recover safely from failed tool calls.

Days 9–11

Technical simulations

·Complete two timed exercises
·Run one architecture/product mock
·Practice follow-up pressure

Days 12–14

Stories and final loop

·Prepare six quantified ownership stories
·Rehearse project deep dive
·Prepare interviewer questions

Practice these

Where people slip

!Generic enthusiasm about startup culture or AI
!No understanding of the company business model
!Ignoring Indian price sensitivity, regulation or operational variance
!Architecture without failure recovery and observability
!Claiming a recommended case was actually asked

Ask them this

?What is the exact loop for this team and level?
?Which rounds permit AI tools?
?What would I own in the first 90 days?
?What is the hardest product or model constraint the team faces in India?
?How does the team measure quality after launch?
?How are ESOPs valued and what is the exercise policy?