AI Engineer
2 weeks ago
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 startup 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
- 3+ years of experience in AI/ML, NLP, or backend system design
- Strong Python engineering fundamentals and practical experience with
LangGraph
,
LangChain
, or similar agent frameworks - Comfortable building
MCP-style architectures
— where agents reason with structured inputs, manage context, and follow execution protocols - Experience with
LLM APIs
(OpenAI, Anthropic, Claude), prompt engineering, and managing token/latency trade-offs - Familiarity with
vector search engines
(Pinecone, Chroma, Weaviate) and
RAG-based retrieval systems - Bonus: background in
clinical NLP
,
medical coding standards
(ICD-10, CPT), or exposure to
FHIR/HL7 - Startup mindset: autonomous, fast-moving, curious, and deeply pragmatic
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.
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