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.
Requirements
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.
Benefits
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.
