Amigo builds AI agents for healthcare—systems that handle patient conversations, take clinical actions, and escalate to humans when needed.
Our agents operate autonomously within bounded clinical domains. Clear inclusions, exclusions, and handoff protocols. The scope of autonomous operation expands over time as we validate performance across patient populations.
We own the data foundation end-to-end: patient interactions, agent reasoning traces, outcome data, and synthetic data with known fidelity. This enables population-level analytics and continuous improvement.
Series A from leading investors. Clinical validation and evidence generation in partnership with leading academic medical institutions.
About this roleAs a Staff Software Engineer (Data) at Amigo, you'll own the technical direction of our data platform—a strategic differentiator that powers agent improvement, clinical analytics, and research collaboration. You'll architect streaming and batch infrastructure on Databricks that processes agent conversations, clinical events, and patient outcomes at scale.
We own the entire data foundation: raw interaction data, agent reasoning traces, clinical outcomes, and high-fidelity synthetic data. You'll drive architecture decisions for population analysis, data mining pipelines, the Research Platform backend, and secure data sharing with academic partners.
What you'll doOwn technical architecture for the data platform across Databricks, Delta Lake, and supporting infrastructure
Drive engineering standards for pipeline reliability, data quality, and observability
Architect streaming and CDC pipelines that power real-time analytics and agent feedback loops
Design the data backend architecture for Research Platform, including natural language query capabilities
Architect data mining systems for persona discovery, scenario extraction, and edge case detection
Design anonymization and data sharing infrastructure for research partnerships with academic medical institutions
Own multi-region data architecture and compliance requirements
Make build vs. buy decisions for data tooling and evaluate technical tradeoffs
Mentor engineers and establish patterns that raise the bar for the data team
Collaborate with data scientists, agent engineers, and clinical operations to align data capabilities with business needs
7+ years of production data engineering experience, with significant time at high-caliber engineering organizations
Expert-level experience with Databricks, Spark, and Delta Lake at scale
Strong Python and SQL skills with deep understanding of distributed data systems
Proven track record designing data architectures that scale
Deep experience with streaming systems, CDC patterns, and real-time data processing
Strong understanding of data modeling, medallion architecture, and query optimization
History of establishing engineering standards and mentoring engineers
Extremely high standards for data quality, reliability, and operational excellence
Both execution-oriented and defensive-minded: you ship infrastructure while anticipating failure modes
Excellent communication across engineering, data science, and executive stakeholders
Experience with healthcare data platforms or HIPAA compliance at scale
Background architecting multi-tenant data systems with strict isolation requirements
Experience building natural language query interfaces or LLM-powered data tools
Track record with ML infrastructure (feature stores, training pipelines, model serving)
Experience with Delta Sharing or cross-organization data collaboration
Knowledge of vector search systems and embedding infrastructure at scale
Comprehensive health, dental, and vision insurance
Mental health support and wellness coaching
Flexible wellness stipend for fitness, therapy, or personal growth
Daily catered lunch and dinner
Annual learning budget for courses, books, or conferences
Conference attendance budget for professional development
Development setup of your choice
Academic collaboration opportunities
Top Skills
What We Do
Amigo AI builds trust and safety infrastructure for clinical agents—ensuring AI systems in healthcare provide quantified confidence when mistakes aren't an option. Our platform combines advanced simulation, verification, and recursive optimization to enable healthcare organizations to deploy AI with statistical guarantees about its behavior.
We solve the fundamental challenge of reliable AI in critical domains through deterministic verification for clinical protocols and continuous drift detection for real-world performance. Our systems provide complete transparency—every AI decision is traceable and auditable, with quantified confidence intervals rather than black box predictions.
Founded by technologists from Google, Meta AI, Databricks, Coda, and Plaid, we've built systems that let organizations make informed risk decisions about AI deployment in healthcare. Our interdisciplinary approach draws from computer science, economics, physics, and mathematics to tackle human-centric optimization problems where people and populations are at the center of every solution.
We're actively working with healthcare organizations across digital health, cancer care, cardiac care, and personalized medicine to deploy AI systems that continuously learn and adapt from real-world feedback while maintaining verified safety boundaries. Our technology amplifies human expertise rather than replacing it, empowering domain experts to achieve outcomes neither could accomplish alone.
Why Work With Us
We build AI healthcare systems where 99% isn't good enough. Rapid growth—promotions in 3 months. Freedom to work your way: art museums or late nights. Tackle recursive optimization problems that ship to production. Your work directly impacts critical healthcare decisions. Diverse team from Google, Meta AI, Databricks solving problems that matter.
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