What are the responsibilities and job description for the AI Product Onwer position at Mango Analytics?
Role: Product Owner – AI Solutions
Work Location: Charlotte, NC (Hybrid onsite; local candidates preferred)
Duration: Long Term Contract
Experience: 8–12 years
Role Summary
The Product Owner will partner with business and technology teams to take AI and agentic AI solutions from initial problem framing through production release and adoption. The role owns use-case intake, prioritization, backlog management, acceptance criteria, evaluation KPIs, governance readiness, and measurable business outcomes.
Key Responsibilities
- Facilitate business problem framing and identify suitable AI, LLM, RAG, or agentic solutions.
- 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 workflows.
- 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.
- Knowledge of 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