Company interview guide

LimeChat

All AI roles · updated 2026.07

Limited public evidence

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

4

stages

2–5 weeks

end to end

20

practice questions

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  • 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

01

The interview, stage by stage

  1. 1

    Founder or hiring manager screen60 min

    workflow automationcustomer discovery

    Prepare one quantified example demonstrating workflow automation.

  2. 2

    Practical role exercise60 min

    customer discoverytool reliability

    Prepare one quantified example demonstrating customer discovery.

  3. 3

    Technical/product deep dive60 min

    tool reliabilityevaluation

    Prepare one quantified example demonstrating tool reliability.

  4. 4

    Team values and ownership round90 min

    evaluationenterprise deployment

    Prepare one quantified example demonstrating evaluation.

02

What decides the offer

Workflow automation

25%

Shows specific decisions and measurable evidence for workflow automation.

Customer discovery

20%

Shows specific decisions and measurable evidence for customer discovery.

Tool reliability

20%

Shows specific decisions and measurable evidence for tool reliability.

Evaluation

20%

Shows specific decisions and measurable evidence for evaluation.

Enterprise deployment

15%

Shows specific decisions and measurable evidence for enterprise deployment.

They look hardest for workflow automation, customer discovery, tool reliability, evaluation.

03

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 workflow automation
  • ·Practice customer discovery
  • ·Practice tool reliability

Days 6–8

Company-context cases

  • ·Turn a vague support workflow into an agent.
  • ·Set human-escalation boundaries.
  • ·Prove ROI without gaming automation metrics.

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

04

Practice these

05

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

06

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?

Sources