Lead AI/ML
5 days ago
Opportunity to work with our client who is building the AI foundation for value-based healthcare — we're hiring an AI/LLM Technical Lead to architect next-gen Agentic AI systems transforming how healthcare is delivered.
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
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