Overview
Skills
Job Details
- Define, design, and implement Agent-to-Agent (A2A) protocols to allow autonomous collaboration, negotiation, and task delegation between specialized agents (e.g. ClaimsAgent, EligibilityAgent, ProviderMatchAgent)
At least 7 years of applied AI experience, especially in LLMs, transformer architectures, agents, or advanced NLP in applied settings
Demonstrated hands-on experience building or deploying Agent-to-Agent protocols, multi-agent orchestration tools (LangGraph, AutoGen, CrewAI, or equivalent)
Experience designing and operationalizing Model Context Protocol (MCP) or similar long-term memory & context systems for agents
Strong software engineering skills in Python and proficiency in frameworks/libraries such as Hugging Face Transformers, PyTorch, LangChain, spaCy, etc.
Domain knowledge in healthcare / benefits: claims systems, eligibility rules, clinical data, structured standards like FHIR, HL7, ICD/CPT, X12 EDI
Cloud-native experience (AWS / Azure / Google Cloud Platform), containerization (Docker / Kubernetes), CI/CD, and deployment of model pipelines
Excellent communication, problem-solving skills, and ability to engage across technical and domain teams