Senior Applied AI Engineer [NYC or SF]

AMIGO

San Francisco, USonsite$200k-$260k/yrPosted Jul 29, 2026
Posting intelligenceActively listed

Skills

ml

About the role

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 Senior Applied AI Engineer 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 role at the intersection of engineering, product, and the customer.

What you'll do

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

Making the calls on tradeoffs: what to build now, what to reuse, and what to push back on

Working directly with customers to keep scope, timelines, and quality honest

What we're looking for

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 or San Francisco

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

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

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.

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.

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.

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.

Compensation Range: $200K - $260K

Compensation

This Machine Learning Engineer role pays $200k-$260k/yr. Within typical range for machine learning engineer roles in United States.

Questions about this role

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