Associate AI Automation Engineer

We’re building the future of healthcare automation — starting with the post-acute, value-based care space , where both medication overload and revenue cycle complexity are driving unnecessary costs and poor outcomes. Founded by Dev Roy (2x exited founder), our stealth start-up is building multi-agent LLM systems that operate with transparency, accuracy, and traceability — tackling two of the hardest problems in the healthcare stack : medication optimization and revenue cycle management (RCM) .

We use LangGraph and a tightly structured MCP (Model-Context-Protocol) architecture — where agents don’t just generate text, but operate over stateful contexts , issue tool calls , and follow explicit protocol-guided reasoning loops . The agents we build don’t guess — they explain, document, and prove.

Responsibilities

• Architect and implement multi-agent systems using LangGraph, leveraging an MCP-inspired structure : agents with memory, contextual tool use, and protocol-defined responsibilities
• Build workflows that replicate expert-level medical coding and medication review processes
• Design tool interfaces (e.G. vector DB, ICD-10 knowledge graph, FHIR endpoints) and integrate them into agents’ decision-making loops
• Orchestrate LLM calls with clear traceability, structured state, and logging for regulatory-grade auditability
• Own experiments and iterate rapidly to improve reasoning, accuracy, and output alignment
• Collaborate closely with the founder on roadmap, architecture, and product direction

Qualifications

If you want to build human-grade AI agents that actually matter — not chatbots, but reasoning systems that impact clinical decisions and billing integrity — we’d love to talk.