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