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.

Advantages

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.

📌 AI/LLM Technical Lead (Haveli)
🏢 Recognized
📍 Haveli