Lead AI / ML – Build Agentic LLM Systems Powering the Future of Healthcare

Company overview :

Join a fast-growing health-tech company that’s reimagining primary care for the modern world. As the Lead AI / ML Architect , you’ll design and build next-gen Agentic AI systems that enable clinical teams to deliver smarter, value-based healthcare. You’ll lead the architecture for multi-agent orchestration, RAG pipelines, and LLM-driven reasoning frameworks—shaping how millions experience care.

The company recently raised $6 million in funding to scale its AI-first care platform , unifying providers, patients, and workflows across the U.S. healthcare system. You’ll collaborate with top engineers and data scientists to turn AI innovation into real-world healthcare impact —from automating clinical tasks to enhancing care quality and outcomes.

Years of experience : 8-17 Years.

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