Design and develop advanced agentic AI systems, including autonomous, semi-autonomous, and human-in-the-loop solutions.
Lead data engineering and modeling efforts to enable scalable, real-time knowledge retrieval and validation across enterprise systems.
Build and maintain full-stack applications, integrating backend services with React-based frontend interfaces.
Collaborate with cross-functional teams to embed AI solutions into clinical workflows, ensuring reliability and compliance.
Drive architecture decisions, enforce code quality standards, and continuously improve system performance and security.
What's Needed?
3+ years of professional AI engineering experience in RAG and large language model (LLM)-based systems, data engineering, and data modeling (ideally in the clinical trial domain)
Proficiency in Python (backend), React (frontend), and AWS services such as Lambda and DynamoDB.
Hands-on experience with vector search, large-scale document systems, and multi-LLM environments.
Deep understanding of prompting, LLM behavior, and building reliable AI systems in production environments