Build and deploy production-grade AI systems that automate complex clinical workflows and improve patient care delivery. You will design LLM agents, implement RAG systems, and create robust evaluation frameworks for medical documentation. This role offers the opportunity to own the full AI lifecycle in a mission-driven environment where technology directly impacts healthcare outcomes.
Senior Applied AI Engineer at well-funded healthtech AI startup
With top-tier VC backing, a base salary up to $250k, and significant equity, this role offers the rare opportunity to apply cutting-edge AI to high-stakes medical challenges while working alongside a world-class engineering team in a mission-driven San Francisco environment.
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Location
San Francisco, United States
Compensation
$190k-$250k + Equity
Company
Confidential company
Role overview
About the company
Well-funded healthtech AI startup
What you will do
- Design and deploy LLM agents and RAG systems capable of reasoning over complex clinical documentation and context.
- Build rigorous evaluation frameworks and safety guardrails to ensure AI reliability within a highly regulated domain.
- Collaborate with engineering and product leaders to integrate automated reasoning into core healthcare delivery pipelines.
Who this is a fit for
- Has over 5 years of software engineering experience with a proven track record of shipping production-grade LLM applications.
- Demonstrates strong engineering judgment regarding observability, maintainability, and reliability in AI-driven system design.
- Thrives in fast-paced startup environments and possesses the ability to navigate technical ambiguity while maintaining a focus on pragmatism.
Why this role is remarkable
- Work on high-impact AI systems that solve fundamental scaling challenges in the massive home healthcare market.
- Join a high-velocity Series A startup backed by top-tier venture capital firms with deep domain expertise.
- Influence the technical direction and architecture of a platform transitioning manual healthcare operations into automated, AI-native workflows.
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