Insurance Expert - AI Training & Evaluation

This is an internal role at Weekday. Not a role by a client.

• Role type: Project-based / Contract
• Location: Remote
• Compensation: ₹20,000–25,000 per task
• Experience: 3+ years in underwriting, claims, or a closely related insurance role
• Hours: Flexible and task-based — no fixed working days

Weekday is an AI-native recruiting platform. We are backed by Y Combinator and Venture Highway (now General Catalyst). We have built the largest white-collar talent database in India and have built tools to run outbound recruiting campaigns to them.

We are now running an AI training and evaluation project as a YC-backed AI data lab, and we're looking for insurance experts to build and judge the tasks that advanced AI models get tested on.

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.

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