Research Scientist (Clinical)

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 own outcomes, not just delivery. For our customers, we're responsible for agent performance: clinical safety, continuous improvement, measurable patient outcomes. Agents operate autonomously within bounded clinical domains, with clear scope and handoff protocols. That scope expands as we validate performance across populations.

We're backed by Tier 1 investors like General Catalyst, GSV Ventures, SVA, and CohoVC. 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 a Clinical Research Scientist at Amigo, you'll lead research on clinical AI safety, evaluation frameworks, and evidence generation. You'll design studies that validate agent performance across patient populations, develop metrics for clinical quality, and publish findings that advance the field. Your clinical expertise ensures our agents meet the standards required for autonomous operation in healthcare.

This role bridges clinical practice and AI research. You'll work directly with our agent engineering and data science teams to translate clinical knowledge into measurable evaluation criteria and safety guardrails.

• Design and lead clinical validation studies for AI agent performance

• Develop evaluation frameworks and metrics for clinical safety and quality

• Publish research on clinical AI safety and agent evaluation methodologies

• Collaborate with academic medical institutions on research partnerships

• Define clinical protocols and escalation criteria for agent behavior

• Review agent outputs and failure modes from a clinical perspective

• Contribute to regulatory submissions and compliance documentation

• Advise on clinical workflow design and patient safety considerations

• MD or equivalent medical degree with active clinical license

• Clinical experience in primary care, internal medicine, or relevant specialty

• Track record of clinical research and peer-reviewed publications

• Understanding of clinical quality metrics and patient safety frameworks

• Experience with clinical study design and IRB processes

• Ability to translate clinical expertise into technical requirements

• Strong communication across clinical, research, and engineering teams

• Interest in AI/ML applications in healthcare

• Fellowship or additional training in clinical informatics

• Experience with digital health or health technology companies

• Background in quality improvement or patient safety initiatives

• Familiarity with FDA guidance on clinical decision support and AI/ML

• Experience with EHR systems and clinical workflow optimization

• Publications in clinical AI, digital health, or health informatics

• 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

• Annual learning budget for courses, books, or conferences

• Conference attendance budget for professional development

• Annual team offsite

• Academic collaboration opportunities

• Unlimited PTO

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.

• 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.