Founding Product Engineer

We are building AI agents that handle all of the behind-the-scenes work for large specialty clinics, allowing their doctors to deliver lifesaving care faster. Our AI agents do everything from answering clinics’ phones, to getting approval from insurance for patients’ complicated treatment plans.

We're a two-person team with private-equity owned clinics as customers, and we're growing fast. We are looking for teammates who are motivated to build for a world where receiving high quality medical care is as frictionless as Shopify’s checkout.

Role:

• You will be a product engineer, owning entire features across the stack.

• You will be one of the first hires and report to the CTO.

• We are supply constrained; your work will unlock our pipeline worth $millions in revenue.

What we look for:

• You love building and being around builders.

• You seek (and help foster) energizing work environments, with a preference to work hard, in our NYC office, five days a week.

• You strive (key word) to produce zero defect work for our customers.

• You are honest.

• You are kind.

• You are low ego and don’t make excuses.

Our values:

• We are customer obsessed.

• We take responsibility for our work. Things will go wrong, there is no time to play the blame game.

• Our machines learn, and so do our humans. We grow from our mistakes.

• We enjoy each other’s company.

The process:

1. 15-minute chat with Tej (CEO)

2. 45-minute “technical” resume deep-dive and a schema design exercise with Aumesh (CTO)

3. A take-home

4. 1-hour take-home review & coding challenge

5. Work trial (paid)

Benefits:

• Competitive health, dental, and vision plans are fully paid for by the company

• Guideline 401K

• Daily in-office lunch

• Nice gym in-office

Tech stack:

We choose our stack to optimize for performance and iteration speed as we grow. We use React, Typescript, Node.js, Tailwind, and Docker. Our database is PostgreSQL. We experiment with all of the cutting edge LLMs and use most in production for different use cases.

You do not have to have worked with this stack before.