Description

You will drive advanced AI development focusing on large language models and agent architectures.

Responsibilities

• Develop and implement AI agent architectures, including A2A Protocols and Model Context Protocols (MCP).
• Build and refine LLMs and NLP models specifically tailored for healthcare applications (e.g., medical BERT, Bio GPT).
• Implement Retrieval-Augmented Generation (RAG) patterns to enhance model grounding and context.
• Engineer solutions leveraging healthcare data standards such as FHIR, HL7, ICD/CPT, and X12 EDI.

Required Skills

• 10+ years of applied AI experience with focus on LLMs, transformers, or NLP in healthcare.
• Strong Python proficiency with ML/NLP libraries (PyTorch, Hugging Face Transformers, Lang Chain, spaCy).
• Hands-on experience with Agent-to-Agent protocols, Lang Graph, Auto Gen, or Crew AI.
• Practical implementation experience of Model Context Protocols (MCP) for memory management.
• Cloud-native development on AWS, Azure, or GCP, including Kubernetes, Docker, and CI/CD.
• Familiarity with healthcare data standards (FHIR, HL7, ICD/CPT, X12 EDI).
• Experience building with LLMs and NLP models.
• Master’s or Ph.D. in a quantitative field, or equivalent professional experience.

Key Skills

Education

Bachelor's or Master's degrees