Description

Key Responsibilities

Assess business processes, systems, and data landscapes to identify high-impact GenAI opportunities.

Design and own end-to-end AI solution architecture, including LLM selection, agent design, RAG frameworks, integrations, security, governance, and evaluation methodologies.

Lead hands-on implementation efforts and establish engineering and prompt-engineering best practices.

Collaborate with business, IT, security, and engineering teams to align objectives and manage delivery risks.

Drive successful deployment, adoption, and measurement of business outcomes through AI solutions.

Required Skills

Strong experience architecting and implementing Agentic AI systems using LLMs, LangGraph, MCP, and RAG.

Expertise in Python, data ingestion/retrieval, vector databases, and AI application development.

Hands-on experience with Azure AI Foundry, Azure AI Services, or similar AI platforms.

Deep understanding of observability, governance, reliability, workflow orchestration, and context/memory engineering.

Healthcare industry experience

Key Skills

Education

Bachelor's degree