AI/LLM Technical Lead

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.