Strong background in data engineering and architecture for AI-ready data-skilled in curating, chunking, enriching, and governing unstructured and semi-structured corpora for LLM consumption; Hands-on experience with vector databases (e.g., pgvector, Elastic Search), hybrid search, reranking, knowledge graphs, and embedding strategies for high-quality retrieval. Work closely with Solution and Enterprise Architects to develop solution architectures that integrate LLMs, agent frameworks, and AI services into the broader enterprise system, ensuring alignment with Enterprise Architecture principles and non-functional requirements (security, scalability, resilience, token economics, and latency budgets).