Staff Applied AI Engineer [NYC or SF]

Amigo AI

New York (NY)

On-site

USD 130,000 - 160,000

Full time

14 days+

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Benefits offered by this job

Comprehensive health, dental, and vision insurance
Daily catered lunch and dinner
Annual learning budget
Unlimited PTO

Job summary

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.

Qualifications

  • Experience leading engineering teams in tech environments.
  • Ability to break down ambiguous problems into executable tasks.
  • Familiarity with LLMs and agent systems.

Responsibilities

  • Lead AI deployment for healthcare customers.
  • Set architecture and engineering standards for the team.
  • Make decisions on project scope and requirements.

Skills

Leadership
Problem Solving
Experience with LLMs
Judgment for Tradeoffs

Job description

About Amigo

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.

About this role

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.

What you might work on
  • Leading an AI deployment for a major healthcare customer, from first conversation to production
  • Turning an ambiguous customer need into a clear technical plan with owners and timelines
  • Setting the architecture and engineering standards the team builds within
  • Making the calls on tradeoffs: what to build now, what to reuse, and what to push back on
  • Growing the engineers around you and raising the bar of the whole team
  • Working directly with customers to keep scope, timelines, and quality honest
You may be a fit if
  • You’ve led significant engineering work end to end, as a tech lead, staff engineer, or engineering manager
  • You’ve broken hard, ambiguous problems into work other engineers could own and deliver
  • You have real experience with LLMs and agent systems, or the depth to get there fast
  • You have the judgment to make tradeoffs and the standing to say no when something doesn’t hold up
  • You lead well, whether through architecture, through people, or both
  • You’re low ego, direct, and hold yourself and your team to a high bar
  • You can work on site in New York City
Nice to have
  • Experience in a regulated or high-reliability domain (healthcare, finance, legal)
  • Experience shipping production AI or ML systems
  • Background in customer-facing or forward‑deployed engineering
  • Experience growing engineers or running a small team
Benefits (available to Full-Time Employees)
Health & Wellness
  • Comprehensive health, dental, and vision insurance
  • Daily catered lunch and dinner
  • Mental health support and wellness coaching
  • Flexible wellness stipend for fitness, therapy, or personal growth
Growth & Development
  • Annual learning budget for courses, books, or conferences
  • Conference attendance budget for professional development
  • Annual team offsite
  • Academic collaboration opportunities
  • Unlimited PTO
Our Core Values
  1. Patients Win, We Win

    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.

  2. High Standards, High Care

    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.

  3. Thoughtful Urgency

    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.

  4. Intensely Measured

    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.

Who Builds With Us
  • Low ego: Politics and territory don't interest you. The best ideas win, regardless of who has them.
  • Direct: You say the hard thing, challenge ideas openly, and commit fully once decided.
  • High agency: You thrive on trust rather than instruction. When you see something is broken, you fix it. You don’t file tickets and wait for someone else.
  • Bar of excellence: You hold yourself to a bar most people wouldn't, and you want teammates who do the same.
  • Skeptical: You push back on rules that don’t make sense and question assumptions that haven’t earned their place.
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