Description

Key Responsibilities
Facilitate business problem framing and identify suitable AI, LLM, RAG, or agentic solution patterns.
Manage use-case intake, prioritization, feasibility assessment, and roadmap alignment.
Create product epics, user stories, acceptance criteria, and release objectives.
Coordinate data, model, platform, security, risk, and engineering stakeholders.
Define business, model-quality, operational, adoption, and value-realization KPIs.
Support model selection, prompt strategy, RAG design, evaluations, and human-in-the-loop controls.
Ensure responsible AI, security, compliance, and model-risk requirements are addressed.
Drive user acceptance, release readiness, adoption planning, and post-release outcome tracking.
Required Skills
Product management and Agile backlog ownership.
Business problem framing and use-case prioritization.
Understanding of LLMs, RAG, agentic AI, model selection, and evaluation approaches.
Experience defining functional and non-functional acceptance criteria.
Responsible AI, model-risk, security, and governance controls.
Product analytics, adoption metrics, and business-value measurement.
Executive communication and stakeholder facilitation.
Experience working with multidisciplinary AI engineering teams.
Preferred Qualifications
Bachelor’s or master’s degree in technology, business, data science, or a related field.
Product Owner, Scrum, SAFe, or product-management certification.
Experience delivering enterprise AI solutions in a regulated environment

Key Skills

Education

Bachelor's degree