Primary Responsibilities:

AI Integration, Enablement & Governance

Embed AI tools into university systems and business processes to ensure successful adoption.

Integrate Microsoft, Google, and other approved AI services into workflows.

Support onboarding, training, and change management for responsible AI use.

Ensure compliance with Mines data governance and AI policies.

Contribute to AI governance frameworks, including model transparency and risk mitigation.

AI Solutions & Strategy

Develops, deploys, and aligns AI solutions with institutional goals and long-term value.

Identify and fast-track opportunities for AI-driven innovation that enhance academic programs, student experiences, and operational efficiency.

Accelerate the full lifecycle of AI product development, from discovery and prototyping to deployment and iteration.

Understand product roadmaps and assess features, technical feasibility, and overall institutional value.

Translate complex AI concepts (e.g., large language models, prompt engineering, RAG, AIOps) into actionable product strategies.

Develop and track key performance indicators (KPIs) and user feedback to measure the success and impact of AI initiatives.

Stakeholder Collaboration & AI Literacy

Emphasizes cross-functional engagement and building AI fluency across the institution.

Establish relationships and partner with academic, administrative, and IT stakeholders to implement requirements and align AI solutions with institutional goals.

Serve as a liaison between technical teams and end users to ensure clear communication and shared understanding.

Contribute to AI literacy initiatives by developing documentation, training resources, and awareness campaigns for faculty, staff, and students.

Minimum Qualifications

Bachelor's degree from a four-year college or university in computer science, data science, information systems, engineering, or related field. Individuals without a degree may be considered if they demonstrate possession of substantially the same knowledge level as found in a degree but have attained the advanced knowledge through a combination of work experience and intellectual instruction

3+ years of experience in one or more of the following areas:

Product ownership in a technology-driven environment

Artificial Intelligence (AI) architecture or implementation (Can include Machine Learning (ML) development or implementation)

Business analysis or digital transformation

Data analytics, data governance, or data strategy

Technology enablement or IT project management

Strong understanding of AI/ML concepts, including generative AI, prompt engineering, and model evaluation

Ability to translate complex technical concepts into actionable strategies for diverse stakeholders

Familiarity with cloud-based AI platforms (e.g., Microsoft Azure, Google Cloud, AWS)

Knowledge of data privacy and compliance frameworks (e.g., FERPA, HIPAA, GDPR)

Excellent communication, collaboration, and stakeholder engagement skills

Demonstrated ability to lead cross-functional initiatives and drive organizational change

Eagerness to learn Agentic AI skills that will immediately be put to use

Self-starter with a high degree of initiative, accountability, and adaptability

Preferred Qualifications:

Master’s degree in a related field

Experience managing AI or data-driven products in complex, regulated environments

Experience in higher education, research institutions, or public sector organizations

Hands-on experience with AI/ML development processes, including model evaluation, prompt design, and iterative testing

Experience contributing to or leading AI governance initiatives, including model transparency and risk mitigation

Certified Scrum Product Owner (CSPO)

Information Technology Infrastructure Library (ITIL) for IT Service Management

Project Management Professional (PMP)

Microsoft Certified: Azure AI Engineer Associate

Google Cloud Professional Machine Learning Engineer

Certified Analytics Professional (CAP)

Familiarity with AIOps tools and practices for continuous integration and monitoring of AI systems

Strong knowledge of Microsoft 365 Copilot, Google Gemini Enterprise, and other enterprise AI tools

Proficiency with Agile methodologies and product management tools