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Amigo AI in New York City is seeking an Applied AI Tech Lead to drive customer deployments and set technical direction. The ideal candidate will possess strong leadership skills and technical expertise in AI deployment, turning ambiguous challenges into concrete plans.
This role focuses on liaising with customers and engineering teams to ensure successful project delivery while maintaining high standards and quality. Benefits include comprehensive health insurance and an annual learning budget.
Amigo partners with healthcare organizations to deploy robust AI infrastructure that directly serves patients and providers. Our agents handle clinical workflows and patient engagement across the entire journey: pre-visit intake, care navigation, post-visit care plans, patient monitoring, and more.
We’re fresh off our Series A backed by Tier 1 investors like Madrona, General Catalyst, and Optum Ventures. Our work is validated with leading academic medical institutions. Our agents have reached 3M+ patient encounters and are on track to 10x this year.
As an Applied AI Tech Lead at Amigo, you’ll lead the technical delivery of customer deployments end to end. You’ll set the architecture, break big ambiguous problems into work a team can own, commit the timelines, and hold the bar for what ships. It’s a hands‑on leadership role at the intersection of engineering, product, and the customer.
Depending on your strengths, the role leans toward deep technical leadership, people leadership, or both. Some tech leads are the deepest technical authority on the team and take the hardest problems themselves. Others manage a handful of engineers and own how the team operates. Most do some of each. We work out the shape with you.
If patients aren't getting better care, we haven't earned the right to scale. Every internal decision gets pressure‑tested: does this make patients' lives better? If we can't draw the line, we question why we're doing it.
We hold a high bar for the team because patients are counting on us to get this right. But high standards only work with genuine investment in each other. You can take risks, admit mistakes, and challenge ideas—not despite our standards, but because of them.
We move fast by default, but speed without judgment is recklessness. The discipline is knowing which decisions are reversible vs. not. In healthcare AI, the companies that win will be fast everywhere they can be and careful everywhere they must be. We build the muscle to do both.
We instrument patient outcomes, provider ROI, system performance, and clinical accuracy. But data without action is surveillance. Every metric should have an owner, a threshold, and a response plan. If we're measuring something but never acting on it, we stop measuring it.