Lead the architecture, development, and deployment of LLM-based and agentic AI systems for healthcare and operational applications. Oversee multi-agent orchestration, RAG pipelines, prompt engineering, evaluation, monitoring, and hallucination mitigation. Collaborate with product, data, design, customers, and clinical stakeholders; lead Scrum delivery, mentor engineers, support hiring, and ensure HIPAA, PHI safety, and responsible AI compliance.
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.
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.
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