Role- Senior Data Scientist
Location- Mason, OH
12+ Months
In person Interview is must
Must-
• AI agent architectures, LLMs, NLP developing A2A
Protocols and Model Context Protocols (MCP)
• LLMs and NLP models (e.g., medical BERT, BioGPT)
• Retrieval-augmented generation (RAG)
• Coding experience in Python, with proficiency in ML/NLP
libraries
• AWS, Azure, or GCP including Kubernetes, Docker, and CI/CD
Bonus
Healthcare data standards like FHIR, HL7, ICD/CPT, X12 EDI formats.
We are seeking a Senior Data Scientist with deep expertise in LLMs, NLP,
and agent architectures to lead the development of interoperable,
self-improving AI agents in the healthcare domain. This role focuses on
designing advanced multi-agent systems that interact intelligently
across clinical, administrative, and benefits platforms using
Agent-to-Agent (A2A) protocols and Model Context Protocols (MCP).
Key Responsibilities
• Design and implement A2A protocols for autonomous task
delegation and collaboration among specialized AI agents (e.g.,
ClaimsAgent, ProviderMatchAgent).
• Develop MCP pipelines to enable persistent memory and
context continuity across multi-turn healthcare interactions.
• Architect and deploy LLM-orchestrated agent systems for
use cases like prior authorizations, benefit optimization, and clinical
summarization.
• Fine-tune domain-specific LLMs and NLP models (e.g.,
medical BERT, BioGPT) for intent classification and personalized
recommendations.
• Build retrieval-augmented generation (RAG) systems with
structured/unstructured healthcare data (e.g., FHIR, ICD-10, EHR).
• Collaborate on building scalable, secure, and compliant
ML pipelines (HIPAA, CMS, NCQA).
• Lead research in memory-based agents, RLHF, and
context-aware planning.
• Contribute to end-to-end MLOps pipelines for deployment,
monitoring, and iteration.
Required Qualifications
• Master’s/Ph.D. in CS, ML, NLP, or related field.
• 7+ years in applied AI, particularly with LLMs,
transformers, or agent systems in healthcare.
• Proficiency with tools like LangGraph, AutoGen, CrewAI,
and hands-on A2A protocol development.
• Proven experience with Model Context Protocols, LLM
pipelines, and healthcare NLP.
• Strong Python skills with libraries such as Hugging Face,
LangChain, spaCy, and PyTorch.
• Understanding of healthcare systems (e.g., claims,
eligibility, plan design).
• Experience with healthcare data standards: FHIR, ICD/CPT,
HL7, X12 EDI.
• Cloud-native development: AWS/GCP/Azure,
Docker/Kubernetes, CI/CD.
Preferred Qualifications
• Expertise in MCP + VectorDB for agent memory and dynamic
context retrieval.
• Experience building production-grade LLM agents in
healthcare.
• Background in voice AI, AI navigation, or triage systems.
• Published work or patents in LLM-based agent systems or
contextual AI.
Thanks
Yashasvi Hasija
Technical Recruiter | Empower Professionals
…………………………………………………………………………………………………………………….
Yashasvi@empowerprofessionals.com