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

• Designs end-to-end Artificial Intelligence (AI) solutions, including data ingestion, model training/fine-tuning, deployment, monitoring, lifecycle management, and machine learning architectures
• Leads the development of AI initiatives from Proof of Concepts (PoCs) to scalable, enterprise-wide production deployments
• Evaluates and recommends AI technologies, including Deep Learning, Natural Language Processing (NLP), Computer Vision, and Generative AI
• Leads design of AI architectures, Large Language Model/Retrieval-Augmented Generation (LLM/RAG) pipelines, and agentic workflow orchestration aligned to business use cases
• Defines AI strategy, roadmaps, and technology standards by evaluating emerging AI/ML technologies
• Balances hands-on AI model development with cross-functional coordination

Artificial Intelligence Architect – Senior/Lead

• 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

• Lead the enterprise AI activation and transformation function, including building and guiding a team responsible for AI strategy, enablement, and execution.
• Establish a long-term vision that balances innovation with responsible adoption.
• Translate enterprise priorities into a clear, actionable AI strategy.
• Identify opportunities to re-engineer business processes using AI, from problem identification through implementation and value realization.
• Balance near-term productivity gains with longer-term innovation efforts across a diversified AI portfolio.
• Lead BECU’s internal AI innovation incubator that operates as an internal VC fund, identifying internal opportunities to drive change, funding them, and tracking them as part of the broader AI portfolio.
• Oversee AI governance, including policies, standards and decision frameworks that enable responsible and scalable adoption.
• Partner with leaders across business, technology, and operations to embed AI into real workflows.
• Establish and evolve enterprise AI governance, including policies, standards, and decision frameworks that ensure ethical, compliant, and scalable AI adoption.
• Build organizational capability through education, coaching, and enablement—helping employees develop confidence and fluency in AI tools.
• Influence senior leaders and manage cross-functional partnerships, ensuring alignment with regulatory expectations, risk tolerance, and member trust.

VP, AI Transformation

• Set the multi-year strategy for ML, data, and BI
• Build and scale the Data Science / AI, Data Engineering, and BI Engineering organization
• Manage managers and tech leads
• Run performance management, career development, and retention
• Operate as a peer to VP-level leaders across various functions
• Own the architecture, deployment, and operation of the production ML

VP of AI, ML and Data Strategy

• Drive end-to-end delivery of production AI platforms
• Lead solution architecture, orchestrate model pipelines, and design multi-agent workflows
• Create reusable SDKs and frameworks
• Collaborate across product, engineering, security, and governance teams
• Ensure AI systems are scalable, observable, cost-efficient, and compliant
• Define design patterns and optimize operational pipelines
• Enable internal reuse of proven solutions
• Own the full lifecycle from architecting secure, compliant solutions to deploying and scaling them in production
• Work with Azure OpenAI, Azure AI Search, multi-agent orchestration, and API integrations for EHR, CRM, and member portals

Senior Artificial Intelligence Engineer

• Build, test, and deploy automation, monitoring, and analysis solutions for agent workflows
• Support deployment and scaling of automated agent-based solutions across development and production environments
• Investigate technical, operational, and reliability issues during development and implementation
• Build and integrate software tools that improve system reliability, observability, and scalability
• Support setup of development and production environments, including deployment-related activities
• Develop best practices and methodologies for provisioning, configuration management, monitoring, and troubleshooting
• Collaborate with delivery teams to define and track service level indicators, service level objectives, SLAs, and error budgets
• Create and recommend process improvements that increase stability, efficiency, and operational readiness
• Contribute to the ongoing improvement of operational processes for automated agent workflows

Senior Artificial Intelligence Operations Specialist

• 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

Senior AI/ML Scientist

• Architect internal productivity revolution and analyze workflows.
• Rapidly prototype and refine agentic solutions.
• Help build and deploy production grade AI agents.
• Integrate AI agents with enterprise resources.
• Define and track productivity & ROI.
• Stay at the forefront of AI developments in the media industry.

Artificial Intelligence jobs in South Carolina

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