Applied AI Engineer

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 an Agent Engineer at Amigo, you'll implement production AI agents using our architecture and verification framework. You'll work directly with clinical teams and enterprise customers to build agents that handle complex, specialized services with measurable reliability. This role requires strong technical implementation skills combined with the ability to translate domain expertise into working systems that maintain perfect compliance in regulated environments.

• Implement context graphs that enable agents to select the right reasoning mode (lookup, pattern recognition, exploration) based on problem complexity

• Build and optimize agent configurations, including static personas, dynamic behaviors, and functional memory systems

• Design bounded Operational Patient Domains (OPDs) with explicit inclusions, exclusions, capabilities, and escalation rules

• Implement verification loops and simulation-based testing to validate agent performance against customer KPIs

• Write Python code for tool integrations and API orchestration within customer environments

• Build evaluation suites that gate deployments using customer-specific success metrics

• Collaborate with domain experts through structured interviews to capture reasoning patterns and clinical protocols

• Support technical power users through git-based workflows for rapid iteration

• Implement adversarial testing to systematically identify and prevent failure modes

• Ensure agents maintain audit-ready provenance with version pinning and evidence links

• Contribute to systematizing implementation patterns across different problem domains

• 2+ years of production software engineering experience

• Strong Python skills including proper use of typing, and experience building highly reliable systems that interact with external APIs (schema design, retry strategies, error propagation)

• Experience with LLMs, prompt engineering, and building on AI platforms

• Ability to implement systems with strict reliability requirements

• Understanding of testing and verification methodologies

• Experience working directly with customers or stakeholders to deliver technical solutions

• Familiarity with git workflows and collaborative development

• Strong debugging and problem-solving skills for complex systems

• Ability to balance theoretical concepts with practical implementation constraints

• Clear technical communication for both engineering and non-technical audiences

• Experience in regulated industries (healthcare, finance, legal)

• Background with simulation, synthetic data, or evaluation frameworks

• Understanding of distributed systems and service-oriented architectures

• Experience with observability and monitoring in production environments

• Familiarity with compliance requirements (HIPAA, SOC 2, GDPR)

• 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.