Responsibilities

• Lead architecture, design, and implementation of LLM-based and agentic AI systems for clinical and operational use cases.
  
• Oversee the development of multi-agent orchestration frameworks (reasoning, planning, and task execution) using tools such as LangGraph, CrewAI, or Semantic Kernel.
  
• Build scalable RAG pipelines and retrieval systems using vector databases (Pinecone, FAISS, Weaviate, Vertex AI Matching Engine).
  
• Guide engineers on prompt design, model evaluation, multi-step orchestration, and hallucination control.
  
• Collaborate with product managers, data engineers, and designers to align AI architecture with business goals.
  
• Manage end-to-end AI lifecycle — data ingestion, fine-tuning, evaluation, deployment, and monitoring on Vertex AI / AWS Bedrock / Azure OpenAI.
  
• Lead scrum ceremonies, sprint planning, and backlog prioritization for the AI team.
  
• Work directly with external stakeholders and customer teams to understand requirements, gather feedback, and translate insights into scalable AI solutions.
  
• Ensure compliance with HIPAA, PHI safety, and responsible AI governance practices.
  
• Contribute to hiring, mentoring, and upskilling the AI engineering team.
  
  
  
  

Must-Have Skills

• Deep expertise in LLMs, RAG, and Agentic AI architectures, including multi-agent planning and task orchestration.
  
• Hands-on experience with LangChain, LangGraph, CrewAI, or Semantic Kernel.
  
• Strong proficiency in Python, cloud-native systems, and microservice-based deployments.
  
• Proven track record of leading AI projects from concept to production, including performance optimization and monitoring.
  
• Experience working with healthcare data models (FHIR, HL7, clinical notes) or similar regulated domains.
  
• Experience leading agile/scrum teams, with strong sprint planning and delivery discipline.
  
• Excellent communication and collaboration skills for customer-facing discussions, technical presentations, and cross-team coordination.
  
• Deep understanding of prompt engineering, LLM evaluation, and hallucination mitigation.
  

General Skills

• Strong leadership, mentorship, and people management abilities.
  
• Excellent written and verbal communication for both technical and non-technical audiences.
  
• Ability to balance technical depth with product priorities and delivery timelines.
  
• Adaptability to fast-changing AI technologies and ability to evaluate new tools pragmatically.
  
• A bias toward ownership and proactive problem-solving in ambiguous situations.
  
• Empathy for end-users and a commitment to responsible AI in healthcare.
  

Good to Have

• Experience leading AI platform initiatives or building internal AI tooling.
  
• Exposure to MLOps, continuous evaluation pipelines, and observability tools for LLM systems.
  
• Knowledge of multi-modal AI (text + structured + image data).
  
• Prior experience integrating AI into production SaaS platforms or healthcare systems.
  
  
  
  

Why Join Fold Health

• Lead the development of next-generation AI systems transforming healthcare delivery.
  
• Collaborate with world-class data, product, and clinical teams on meaningful challenges.
  
• Shape the AI roadmap and mentor a growing team of engineers in an innovation-first culture.
  
• Work on cutting-edge Agentic AI and LLM applications deployed in real-world healthcare settings.