Design, build, evaluate, and operationalize enterprise-grade AI and Generative AI solutions supporting the DS/ML AI Accelerator. Partner with data owners and business stakeholders to onboard approved documents, knowledge assets, and data sources into governed AI knowledge repositories. Develop Retrieval-Augmented Generation (RAG) pipelines, metadata strategies, tagging frameworks, retrieval mechanisms, and source citation capabilities.
Create evaluation datasets and retrieval quality metrics to assess relevance, grounding, accuracy, and completeness of AI-generated outputs. Ensure generated content clearly distinguishes factual information, assumptions, inferences, and areas requiring SME validation. Design and implement secure multi-agent AI workflows leveraging LLMs, retrieval systems, APIs, and deterministic processes.
Define agent roles, workflow orchestration, tool integrations, validation rules, error handling, and human-in-the-loop review processes. Develop reusable prompts, workflow patterns, and orchestration frameworks to improve scalability, governance, and user adoption. Establish technical and business-oriented A