• - Design, develop, and deploy LLM-based applications for clinical and operational workflows (summarization, chat, reasoning, data extraction).
  
• - Implement and optimize RAG (Retrieval-Augmented Generation) pipelines with vector databases (FAISS, Pinecone, or Vertex AI Matching Engine).
  
• - Work hands-on with LLM APIs (OpenAI, Claude, Gemini, Mistral, Llama) for fine-tuning, evaluation, and productionization.
  
• - Build and maintain AI microservices / APIs using FastAPI or Flask, integrated with Fold’s Unity platform.
  
• - Implement Agentic AI workflows (multi-step reasoning, tool use, and task orchestration) using frameworks such as LangGraph, CrewAI, or Semantic Kernel.
  
• - Collaborate with the Data Engineering and Product teams to ensure seamless integration of models with curated EHR and FHIR data.
  
• - Conduct model evaluation and benchmarking (factual accuracy, hallucination control, latency).
  
• Follow HIPAA-compliant development practices and ensure PHI safety and responsible AI usage
  
  
  
  

Must have:

• Knowledge of Agentic AI use cases — autonomous task handling, reasoning chains, planning-execution loops.
  
• Understanding of healthcare data formats (FHIR, HL7, clinical notes) is highly preferred.
  

• Knowledge of MLOps, continuous evaluation pipelines, or model observability.
  
• Experience integrating AI features into SaaS or API-first products.
  
• Prior exposure to healthcare AI, clinical NLP, or population health analytics