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

• Define and drive the strategic direction and operational execution of Artificial Intelligence capabilities
• Own the development, communication, and execution of the enGen AI roadmap
• Drive AI adoption and programs within enGen and across the enterprise
• Commercialize enGen's AI capabilities to identify and seed new revenue streams
• Create and nurture strong partnerships across the enterprise and within enGen
• Deliver flexible, high-quality AI solutions and operational frameworks adhering to privacy policies

VP AI Strategy – Enablement

• Serve as the lead AI/ML technical expert supporting data-driven operations across planning, execution, and assessment activities for Combatant Commands (CCMDs).
• Design, develop, and deploy machine learning, artificial intelligence, and advanced statistical models to support operational analysis, campaign assessment, and decision support.
• Develop and operationalize AI-enabled capabilities that automate data ingestion, processing, and analysis across structured and unstructured data sources.
• Build and maintain scalable model pipelines and architectures supporting cross-domain and enterprise-level data integration.
• Apply AI/ML techniques (e.g., predictive modeling, clustering, natural language processing, network analysis) to identify patterns, trends, narratives, and adversary behaviors in the information environment.
• Integrate AI/ML outputs into operational workflows, enabling support to planning, integration, data operations, assessment, and operational execution.
• Collaborate with planners, Assessment Integrators, Data Scientists, and operational staff to translate analytic outputs into actionable insights for decision-makers.
• Develop and support AI-enabled dashboards, decision-support tools, and analytic platforms that provide real-time or near-real-time insights.
• Support the development of reusable models and frameworks that can scale across multiple CCMDs and mission sets.
• Ensure models are transparent, explainable, and aligned to mission requirements, including measurement of effectiveness and operational impact (ROI-informed outputs).

Senior AI Modeling Specialist

• Own and grow a dedicated web property — driving user acquisition, engagement, and community health
• Build and nurture an active community of CISOs and security practitioners around AI agents
• Develop community programs that encourage contribution, peer review, and knowledge sharing
• Support planning and execution of field events — CISO and practitioner regional meetups focused on AI in security
• Create engagement campaigns that drive awareness and adoption of the dedicated web property
• Monitor community health metrics and report on growth, engagement, and sentiment
• Ship content updates, features and user experience improvements for the dedicated web property
• Gather community feedback to inform product direction and content strategy

Community Manager

• 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

• Be responsible for the end-to-end technical delivery of complex AI solutions, personally writing critical code, configuring systems, and troubleshooting issues, while also guiding and reviewing the work of junior team members to ensure successful deployment and measurable business impact
• Take primary ownership of designing, developing, and personally implementing high-quality, scalable production systems
• Work directly with customers to design and build custom intelligent agents using the Agentforce platform, ensuring they precisely meet unique business requirements and integrate seamlessly with existing customer ecosystems
• Own the entire data lifecycle, from strategic design of data models to hands-on building of efficient processing pipelines and establishing seamless integration strategies
• Identify, analyze, and directly resolve the most complex technical challenges during all phases of solution delivery
• Lead the development of bespoke intelligent agents, automate intricate business processes, and craft intuitive user experiences
• Embed yourself deeply with client teams to truly grasp their operational challenges and strategic goals
• Perform detailed analysis, debugging, and root cause identification for complex system interactions, data flows, and AI model behaviors to optimize performance, ensure reliability, and prevent recurrence of issues
• Quickly develop proofs-of-concept and minimum viable products, often coding alongside client teams to demonstrate capabilities and gather feedback for iterative refinement
• Directly apply and evangelize engineering best practices for code quality, scalability, security, and maintainability across all deployed solutions

AI Forward Deployed Engineer – Senior/Lead/Principal

• Own the full AI engagement arc from discovery through sustained workflow adoption
• Drive requirements and delivery precision to track against plans and surface risks early
• Champion continuous quality through testing and feedback loops during AI engagements
• Hold the R&D feedback loop accountable to ensure field learnings flow back
• Build playbooks to identify reusable patterns and scalable frameworks for the team
• Own engagement economics and track cost structure across active engagements
• This is a field-first role with expected travel to partner locations

AI Engagement Manager

• Create and curate a pipeline for sovereign AI across North America
• Explain HPE's solutions aligned with data security protocols to customers
• Provide input to product management and engineering
• Collaborate with sales teams to pursue opportunities requiring high security

Chief Technologist, HPC, AI

• 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

• Lead stakeholders through process mapping and operational improvement
• Own the design, build, and iteration of low-code and AI-enabled workflows
• Translate business needs into reliable, production-grade automations
• Develop and maintain evaluation sets, define quality thresholds, and run A/B tests
• Integrate automation into dashboards and reporting
• Track and communicate impact of automation and AI solutions
• Continuously assess new and existing applications and SaaS platforms
• Lead pilots and proofs of value for new workflows or AI capabilities
• Provide training and enablement to Legal & Compliance teams
• Partner with the Compliance Training team to create AI use case specific policies

Data & AI Operations Manager

• 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.

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