Key Skills and Responsibilities
Expert-level knowledge of NLP, information retrieval, and document understanding techniques
Experience in RAG pipeline optimization including chunking strategies, embedding models, hybrid search (semantic + keyword), and re-ranking
Experience in scientific Design of Experiment to enable objective evaluation of AI experimentations.
Proficiency in defining and building golden datasets, ground truth frameworks, and evaluation metrics (accuracy, precision, recall, KPI thresholds)
Experience scaling AI methods from single use case MVPs to enterprise-grade, multi-use-case deployment
Strong background in agentic AI frameworks and multi-agent orchestration - including expanding agentic approaches beyond Q&A to broader use case coverage
Knowledge of ontology, knowledge graphs, and semantic standards as they apply to enterprise AI solutions
