You will own end-to-end agentic workflows that reason, plan, use tools, and orchestrate multi-agent collaboration in highly regulated healthcare environments
Job Summary
You will own end-to-end agentic workflows that reason, plan, use tools, and orchestrate multi-agent collaboration in highly regulated healthcare environments.
The role involves leading the design of advanced systems using ReAct, CoT, ToT, and emerging protocols like Model Context Protocol (MCP) and Agent-to-Agent (A2A).
You will collaborate with a multidisciplinary team including scientists, clinicians, and former FDA commissioners to foster a data-led public health ecosystem.
Matching Summary
You will own end-to-end agentic workflows that reason, plan, use tools, and orchestrate multi-agent collaboration in highly regulated healthcare environments.
Skills & Requirements
Must-have
7+ years Machine Learning Engineering experience
Production agentic AI system development
LangChain LangGraph and MCP protocol expertise
LLM fine-tuning and deployment on healthcare data
Automated evaluation and safety testing pipelines
Nice-to-have
Rapid prototyping and experimentation mindset
Multi-cloud infrastructure experience
Top AI conference publication record
Deep medical and health domain expertise
Experience with EHRs and claims data
Key Requirements
7+ years hands-on ML engineering experience
Proven track record shipping production agentic AI systems
Strong theoretical foundation in NLP, LLMs, and reinforcement learning