About this role

About the role
Advanced AI models are being pushed into insurance work — underwriting decisions, risk assessment, claims adjudication. Whether they're actually any good at it depends on the quality of the people who train and test them. That's you.

You'll create complex underwriting and claims tasks that a model should be able to handle but often can't, and you'll evaluate what the model produces — where it's right, where it's subtly wrong, and where it's confidently making things up. The work rewards precision. A vague scenario or a lazy evaluation is worse than none at all.

This is not back-office processing and it's not data entry. Each task is a piece of real insurance judgement — the kind of call a senior underwriter or claims assessor would have to get right and be able to defend. If you want templated, repetitive work, this isn't for you. If you like taking a messy risk or a contested claim apart and explaining exactly why a decision is wrong, you'll probably enjoy it.
Requirements
What you'll actually do
On any given task you might be:

Designing a complex underwriting scenario — an application, a risk profile, an eligibility or pricing call — with a clear, defensible model answer
Building claims cases that hinge on coverage determination, policy interpretation, exclusions, or fraud indicators, along with the right adjudication
Reviewing AI-generated underwriting and claims decisions line by line and grading them on accuracy, reasoning, and completeness
Catching misread policy wording, missed exclusions, wrong risk calls, and decisions that sound right but aren't
Writing clear rationales for your evaluations so the model (and the team) learns from them

Every task is reviewed. You'll be measured on the quality and rigour of what you submit, not on volume.
What we're looking for
3+ years of hands-on experience in underwriting, risk assessment, or claims — life, health, general, or specialty lines
Deep working knowledge of how risk is assessed and priced, and how claims actually get decided
Comfort reading policy wordings closely — conditions, exclusions, endorsements — and knowing what they mean in practice
Precision in writing. You say exactly what's wrong and why, without padding
Low tolerance for plausible-sounding nonsense — from a model or anyone else
Reliable on deadlines. Task-based work only works if the tasks come back on time
Curiosity about how AI is going to change insurance work, and a preference for shaping it over watching it happen
What you get
₹20,000–25,000 per task — paid for depth of thinking, not hours logged
Remote, flexible work you can fit around a full-time role
A front-row seat to how frontier AI models are trained and evaluated on insurance work, and a hand in making them better
A YC-backed team that moves fast and keeps things direct
More tasks and larger projects if your work is consistently strong