Senior Data Scientist

We are hiring a Senior Data Scientist with deep expertise in AI agent architectures, large language models (LLMs), natural language processing (NLP), and hands-on experience with Agent-to-Agent (A2A) Protocols and Model Context Protocols (MCP).

This role is critical in building interoperable, context-aware, and self-improving agents that operate across clinical, administrative, and benefits platforms in healthcare.

Key Responsibilities

• Design and implement A2A protocols for autonomous collaboration and task delegation between specialized AI agents (e.g., Claims Agent, Eligibility Agent, Provider Match Agent ).
• Architect and operationalize MCP pipelines to enable persistent, memory-augmented, and contextually grounded LLM interactions.
• Build intelligent multi-agent systems orchestrated by LLM-driven planning modules for benefit processing, prior authorization, clinical summarization, and member engagement.
• Fine-tune and integrate domain-specific LLMs and NLP models (e.g., medical BERT, BioGPT) for document understanding, intent classification, and personalized recommendations.
• Develop retrieval-augmented generation (RAG) systems and structured context libraries for dynamic knowledge grounding across structured (FHIR/ICD-10) and unstructured sources (EHR notes, chat logs).
• Collaborate with engineering and data architecture teams to build scalable, secure, and compliant agentic pipelines.
• Lead research and prototyping in memory-based agent systems, RLHF, and context-aware task planning.
• Contribute to production deployment through robust MLOps pipelines for model versioning, monitoring, and continuous improvement.

• Master’s or Ph.D. in Computer Science, Machine Learning, Computational Linguistics, or a related field.
• 7+ years of experience in applied AI with a focus on LLMs, transformers, agent frameworks, or NLP in healthcare.
• Hands-on experience with A2A protocols and multi-agent orchestration tools (e.g., Lang Graph, Auto Gen, CrewAI).
• Practical experience implementing MCP for long-lived conversational memory and modular agent interactions.
• Strong coding skills in Python and proficiency with ML/NLP libraries (e.g., Hugging Face Transformers, PyTorch, Lang Chain, spaCy).
• Familiarity with healthcare benefit systems, claims data, and eligibility rules.
• Experience with healthcare data standards (FHIR, HL7, ICD/CPT, X12 EDI).
• Cloud-native development experience on AWS, Azure, or GCP, including Kubernetes, Docker, and CI/CD.

• Expertise in MCP + Vector
  
  DB integration for dynamic agent memory and retrieval.
• Experience deploying LLM-based agents in production healthcare systems.
• Exposure to voice AI, automated care navigation, or AI triage tools.
• Published research or patents in agent systems, LLM architectures, or contextual AI frameworks.

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