Description:
Experience Level: 8+ years (with at least 2+ years in GenAI / LLM-based solution design) About the Role We are seeking a RAG Architect to lead the design, development, and optimization of Retrieval Augmented Generation (RAG) systems that integrate LLMs (Large Language Models) with enterprise data sources. The ideal candidate will combine expertise in AI architecture, data retrieval, vector databases, and LLM integration to build scalable, secure, and high-performing GenAI solutions. Key Respons
Oct 24, 2025;
from:
dice.com