Senior Software Engineer (Data)

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 Senior Software Engineer (Data) at Amigo, you'll build the data infrastructure that powers agent improvement, clinical analytics, and research collaboration. You'll own streaming and batch pipelines on Databricks that process agent conversations, clinical events, and patient outcomes at scale.

Our data platform is a strategic differentiator. We own the entire data foundation—from raw interaction data to agent reasoning traces to clinical outcomes. You'll build pipelines that enable population analysis, data mining, and the Research Platform backend.

• Build and maintain streaming and batch pipelines on Databricks (Delta Lake, Spark)

• Design CDC pipelines that sync operational databases to Delta Lake for analytics

• Implement data mining pipelines for persona discovery, scenario extraction, and edge case detection

• Build the data backend for Research Platform, including natural language to SQL capabilities

• Create data quality monitoring, staleness detection, and automated alerting

• Build pipelines for voice and SMS analytics (call quality, engagement metrics)

• Support multi-region data deployment and compliance requirements

• Collaborate with agent engineers and data scientists to surface insights that improve agent performance

• 4+ years of production data engineering experience

• Strong experience with Databricks, Spark, and Delta Lake

• Proficiency in Python and SQL for pipeline development

• Experience building streaming pipelines and CDC (change data capture) systems

• Understanding of data modeling, medallion architecture (bronze/silver/gold), and query optimization

• Experience with data quality frameworks and monitoring

• Track record of building reliable, production-grade data infrastructure

• Both execution-oriented and defensive-minded: you ship pipelines while anticipating failure modes

• Strong debugging skills for distributed data systems

• Clear communication with data scientists, backend engineers, and product teams

• Experience with healthcare data or HIPAA compliance requirements

• Background with ML pipelines (feature engineering, model training infrastructure)

• Experience building natural language query interfaces or LLM-powered data tools

• Familiarity with vector search and embedding pipelines

• Experience with Delta Sharing or data collaboration protocols

• 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.