Senior Data Scientist

Title: Senior Data Scientist AI Agents & LLMs in Healthcare Location: Los Angeles, CA Note: #W2

We are seeking a Senior Data Scientist to join our team in building intelligent, interoperable, and context-aware AI agents that transform healthcare operations. This role focuses on developing advanced agent architectures, leveraging LLMs, and implementing protocols for seamless agent collaboration across clinical, administrative, and benefits platforms.

Key Responsibilities

• Design and implement Agent-to-Agent (A2A) protocols for autonomous collaboration and task delegation between specialized AI agents (e.g., ClaimsAgent, EligibilityAgent).
• Develop and operationalize Model Context Protocol (MCP) pipelines to support persistent, memory-augmented, and contextually grounded LLM interactions.
• Build multi-agent systems orchestrated by LLM-driven planning modules for use cases like benefit processing, prior authorization, and clinical summarization.
• Fine-tune and integrate domain-specific LLMs and NLP models (e.g., BioGPT, medical BERT) for document understanding and personalized recommendations.
• Create retrieval-augmented generation (RAG) systems and structured context libraries for dynamic knowledge grounding from structured and unstructured sources.
• Collaborate with engineering and data teams to ensure secure, explainable, and compliant agentic pipelines aligned with healthcare regulations (HIPAA, CMS, NCQA).
• Lead research and prototyping in memory-based agent systems, RLHF, and context-aware task planning.
• Support production deployment through robust MLOps pipelines for model versioning, monitoring, and continuous improvement.

Minimum Required Qualifications

• Master s or Ph.D. in Computer Science, Machine Learning, NLP, or a related field.
• 10+ years of experience in applied AI, with a focus on LLMs, transformers, agent frameworks, or NLP in healthcare.
• Hands-on experience with Agent-to-Agent protocols and tools like LangGraph, AutoGen, or CrewAI.
• Practical experience implementing Model Context Protocols (MCP) for long-lived conversational memory.
• Strong programming skills in Python, with proficiency in libraries such as Hugging Face Transformers, PyTorch, LangChain, spaCy.

Preferred Qualifications

• Familiarity with healthcare benefit systems, including plan structures, claims data, and eligibility rules.
• Experience with healthcare data standards (FHIR, HL7, ICD/CPT, X12 EDI).
• Cloud-native development experience on AWS, Azure, or Google Cloud Platform, including Kubernetes, Docker, and CI/CD.
• Deep understanding of MCP + VectorDB integration for dynamic agent memory and retrieval.
• Prior work on LLM-based agents in production or large-scale healthcare environments.
• Experience with voice AI, automated care navigation, or AI triage tools.
• Published research or patents in agent systems, LLM architectures, or contextual AI frameworks.