Artificial Intelligence

• Conduct training sessions for SNHU community members to ensure use of AI tools and technologies
• Provide support in the form of hands-on guidance and consultation
• Help optimize existing AI-driven processes to improve operational and educational efficiency
• Collaborate with cross-functional teams to support AI Proofs of Concept, projects, and product exploration
• Assist in brainstorming and planning for faculty and staff ideas related to AI integration
• Develop training materials, guides, and resources to support AI tool adoption across the institution
• Attendance, punctuality, and reliability are essential functions of this role
• Other responsibilities as assigned

AI Integration Specialist

• Serve as EnerSys’ executive leader and single point of accountability for enterprise AI strategy, execution, and outcomes.
• Translate enterprise and business strategies into a clear, multi‑year AI vision and roadmap.
• Advise the CIO, ELT, and Board on AI trends, risks, opportunities, and competitive implications.
• Represent EnerSys externally with strategic AI partners, technology providers, and industry forums.
• Design and implement the enterprise AI operating model, including governance forums and funding processes.
• Establish enterprise standards for responsible AI, data usage, security, privacy, and risk management.
• Own AI investment governance, ensuring alignment with capital planning and transformation funding.
• Own the global AI use case portfolio and prioritization framework.
• Define, track, and report enterprise AI value metrics.
• Orchestrate cross-functional delivery across IT, data, and business units.
• Partner with HR to lead enterprise-wide change management and AI literacy initiatives.
• Build, lead, and develop a high performing enterprise AI organization with clear roles.

VP, Enterprise AI Enablement

• Play a hands-on, operational leadership role in advancing the organization’s applied artificial intelligence strategy across clinical, operational, and administrative domains
• Responsible for the day-to-day management of AI initiatives, supporting the full AI algorithm lifecycle—from intake and evaluation through deployment, monitoring, and optimization
• Work closely with clinical leaders, operational stakeholders, IT, Informatics, Legal, Risk, and external AI vendors to ensure AI tools are safe, effective, compliant, and aligned with organizational goals
• Ensure that AI delivers real, measurable value while maintaining trust, safety, and operational excellence

AI Manager

• Define and evolve enterprise AI Risk and Governance strategy aligned to business outcomes.
• Operationalize a federated governance model with centralized standards and decentralized execution.
• Establish clear decision rights for AI use cases, model deployment, and data usage.
• Own the AI Governance lifecycle including intake, risk tiering, validation, deployment, monitoring, and decommissioning.
• Ensure governance consistency across ML, GenAI, agents, and third-party tools.
• Establish data governance frameworks: ownership, classification, quality, lineage, and compliance.
• Partner with Cyber and Legal on privacy and regulatory adherence.
• Chair and/or participate in key governance forums (Council, Review Board, Architecture Committees) and ensure effective escalation.
• Define and enforce Responsible AI standards including bias, explainability, and control mechanisms.
• Develop and oversee model and agent registry, ensuring lineage, versioning, and performance tracking.
• Embed governance into platforms and pipelines; automate controls and monitoring.
• Define KPIs and ensure governance aligns to measurable business outcomes.
• Support and help drive adoption through enablement, training, and cultural change.

Director, AI Risk and Governance

• Translate business needs into technical systems solutions and architectural roadmaps
• Work on problems of diverse scope and complexity
• Expert in 24/7 operations with high performing systems
• Spearhead research, evaluation and deployment of AI and GenAI capabilities
• Bridge traditional IT Operations with emerging AI technologies
• Collaborate with Infrastructure and Cloud Operations teams to pilot and integrate AI/GenAI features
• Lead research and evaluation of AI and GenAI tools for Infrastructure Operations
• Develop and lead the strategic roadmap for AI adoption in Infrastructure Operations
• Identify automation opportunities and implement AI-enhanced runbooks

Infrastructure Operations Lead – Cloud and AI GenAI Enablement

• Own delivery of large and/or complex ML, DL, and Generative AI systems
• Design, implement, and evaluate AI systems for production
• Apply prescriptive analytics techniques to business problems
• Lead development and testing of ML algorithms
• Stay updated with advancements in AI/ML methods
• Benchmark against existing ML methods
• Develop prototypes and proof-of-concept implementations
• Lead consultation sessions with business partners
• Drive continuous improvement through novel techniques
• Identify actionable insights and communicate results

Artificial Intelligence jobs in Kentucky

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AI Integration Specialist

VP, Enterprise AI Enablement

AI Manager

Director, AI Risk and Governance

Infrastructure Operations Lead – Cloud and AI GenAI Enablement

Senior AI/ML Scientist