Artificial Intelligence

• Assist in the coordination and execution of marketing campaigns, communications, events, and promotional activities.
• Support development and updating of marketing collateral, presentations, email communications, and digital content.
• Help manage project timelines, task tracking, approvals, and distribution of marketing materials.
• Coordinate logistics for webinars, conferences, internal meetings, and client-facing events.
• Maintain organized files, templates, contact lists, and campaign materials using applicable technology tools.
• Collaborate with internal stakeholders to gather information and support timely completion of deliverables.
• Track marketing activities and assist with reporting on campaign performance and operational support needs.
• Provide day-to-day administrative and production support for the marketing function.

AI Marketing & Communications Specialist – AI Practice

• 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

• Translate enterprise technology and business strategies into an actionable portfolio
• Establish execution patterns for AI and automation programs
• Build and run an enterprise operating model that balances execution discipline with agility
• Build executive-grade dashboards and performance views
• Ensure clear adoption ownership and business outcomes for major initiatives
• Lead, coach, and grow SPO leaders, PMs, and execution leads

Staff Vice President – Enterprise Technology Transformation, AI Execution

• Support the preparation, formatting, and assembly of proposals, RFP responses, presentations, and supporting sales materials.
• Coordinate and manage the end-to-end RFP process, including intake, qualification, calendaring, compliance tracking, kickoff coordination, response collection, review cycles, and final submission support.
• Help organize response plans, responsibilities, review cycles, and deadlines to keep proposal and RFP pursuits on track.
• Maintain RFP schedules, requirements matrices, content trackers, and submission checklists to improve consistency, responsiveness, and quality control.
• Coordinate content collection from internal stakeholders and help organize proposal inputs, deadlines, and version control.
• Edit and proofread content to ensure clarity, consistency, accuracy, and adherence to brand standards.
• Maintain proposal content libraries, templates, resumes, case studies, and standard response materials.
• Assist with scheduling meetings, tracking deliverables, and monitoring proposal milestones.
• Collaborate with sales, marketing, and solution teams to help produce polished, client-ready deliverables.
• Support administrative and logistical tasks related to pursuits, client presentations, and business development initiatives.
• Use applicable technology tools to manage documents, shared files, and production workflows efficiently.

Proposal Support – Artificial Intelligence

• Collaborate with the executive leadership team to define the company's CX AI vision, strategy, and goals for contact center transformation
• Drive growth by identifying emerging trends, market opportunities, and industry best practices in contact center innovation
• Lead the planning, development, and execution of the CX AI strategic roadmap, including new innovative offerings in the AI space for contact centers
• Oversee the development and leadership of comprehensive CX AI offerings, including Assistive CX, Agentic CX, Conversation Agents, CX Insights & Intelligence, CCaaS platforms (including Genesys, Five9, AWS Connect, and Google), CRM (Salesforce and Zendesk), workforce management, agent quality management, and technology partnerships (Cresta and ElevenLabs)
• Assume overall accountability for the financial performance of the CX AI practice
• Partner with Business Development, Digital Solutions leaders, and CXM account and operations leaders to grow and transform managed accounts in the BPO business
• In partnership with Business Development, develop and implement effective revenue generation strategies to meet or exceed annual revenue targets for digital contact center solutions
• Monitor financial performance, identify areas for improvement, and implement corrective actions as necessary
• Build and lead high-performing teams across technologies and capabilities
• Foster a culture of excellence, innovation, collaboration, and continuous learning within the CX AI teams globally
• Drive the development and integration of innovative AI-powered solutions and offerings for contact center CX optimization
• Partner with TELUS clients and TELUS Digital stakeholders to drive digital transformation within TELUS-owned CX operations
• Partner with clients to identify their contact center challenges and design tailored digital solutions
• Oversee the delivery of high-quality CX AI implementations and strategic recommendations
• Provide thought leadership and build trusted advisor relationships with key client stakeholders
• Drive the adoption and integration of modern CX platforms and technologies

Managing Director, CX AI Delivery

• Oversee departmental projects and initiatives focused on AI governance maturity, control enhancement, automation, and process optimization
• Facilitate cross-functional risk credible challenge reviews, lead assessment workshops, challenge sessions, and risk-acceptance discussions
• Collaborate on technology initiatives by partnering with Technology, Cybersecurity, Data Governance, and Model Risk
• Design KRIs and monitoring measures (inventory completeness, drift detection, HITL effectiveness, bias testing coverage)
• Author executive summaries and committee-ready narratives translating technical analyses into business impact
• Mentor junior associates and provide coaching, shadowing, and review feedback
• Champion continuous improvement and identify innovation opportunities

Lead AI Risk Advisor

• 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

• Support the operational design and execution of AI agents and multi-agent workflows used across business and technology teams.
• Monitor agent behavior, outputs, and reliability in production environments, identifying performance issues, errors, or unexpected behaviors.
• Tune and optimize agent configurations, prompts, workflows, and execution logic to improve output quality and operational stability.
• Integrate AI agents with enterprise systems, APIs, Model Context Protocols (MCP), and internal or external data sources.
• Implement and maintain runtime guardrails, escalation paths, and human‑in‑the‑loop controls to ensure safe and compliant AI operation.
• Investigate and resolve operational issues related to agent performance, data access, or system integration.
• Document workflows, configurations, and operational procedures to support repeatability and governance.
• Collaborate with AI engineers, data teams, platform teams, and business stakeholders to support the controlled rollout of AI capabilities.

AI Agent Engineer

• Support the operational design and execution of AI agents and multi‑agent workflows used across business and technology teams.
• Monitor agent behavior, outputs, and reliability in production environments, identifying performance issues, errors, or unexpected behaviors.
• Tune and optimize agent configurations, prompts, workflows, and execution logic to improve output quality and operational stability.
• Integrate AI agents with enterprise systems, APIs, Model Context Protocols (MCP), and internal or external data sources.
• Implement and maintain runtime guardrails, escalation paths, and human‑in‑the‑loop controls to ensure safe and compliant AI operation.
• Investigate and resolve operational issues related to agent performance, data access, or system integration.
• Document workflows, configurations, and operational procedures to support repeatability and governance.
• Collaborate with AI engineers, data teams, platform teams, and business stakeholders to support the controlled rollout of AI capabilities.

• Lead design of enterprise AI architecture and reusable platform capabilities
• Define architectural standards, governance models, and best practices for AI implementations
• Evaluate and recommend AI platforms and tooling such as Azure AI services, AWS AI/ML platforms, OpenAI-based solutions, and enterprise LLM platforms
• Develop architecture roadmaps aligned to business strategy and enterprise technology direction
• Guide engineering teams in implementing scalable AI solutions leveraging cloud-native architectures, APIs, and distributed systems
• Design solutions with sufficient technical depth to support implementation and operationalization
• Identify risks and ensure alignment with security, identity, network, and data governance requirements
• Influence decisions around model deployment strategies, integration patterns, and enterprise AI platform design

Senior AI Technology Architect

• Establish and communicate an AI product strategy aligned with business priorities and growth objectives
• Conduct market research, evaluate industry trends, and identify opportunities for AI within financial services
• Translate business needs and user insights into clear product requirements and roadmaps
• Partner with cross-functional teams to support the full product lifecycle, from concept through launch and ongoing enhancements
• Promote responsible AI practices, including ethical considerations, governance, and transparency
• Define and track key metrics to assess product performance and impact
• Share product strategy, updates, and outcomes with leadership and stakeholders
• Stay informed on developments in AI, machine learning, and related technologies, and assess their relevance to the organization
• Support and guide teams in AI product practices, encouraging collaboration and knowledge sharing

VP – AI Product Strategy

• Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies
• Design and evolve information and semantic models that make enterprise data AI‑ready
• Operationalize data models, taxonomies, and semantic structures through the Enterprise Data Catalog (Alation)
• Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures
• Provide authoritative guidance on semantic conflicts
• Contribute to the enterprise data product framework by defining domain boundaries, shared dimensions, and semantic contracts
• Confirm and document prioritized metadata elements for key business processes, analytical use cases, and AI‑enabled workflows
• Identify simplification opportunities—reduce redundancy, converge overlapping datasets, and promote canonical sources
• Partner with analytics, data science, and AI engineering teams to ensure information architecture is sufficient for AI outcomes
• Serve as a thought partner to shape governance strategy and roadmaps.

Knowledge Architect

• Own end-to-end execution of AI initiatives across Consumer & Business Banking, from problem definition through implementation and value realization
• Translate business priorities into a clear, actionable AI roadmap aligned to financial, risk, and strategic outcomes
• Establish and manage structured intake, prioritization, and governance processes
• Drive portfolio alignment, eliminate duplication, and enable reuse of scalable AI capabilities across business lines
• Lead redesign of end-to-end business processes, embedding AI, automation, and analytics into core workflows
• Ensure AI solutions are integrated into frontline workflows to drive measurable productivity and client experience improvements
• Proactively identify and prioritize AI and automation opportunities that improve business performance and client engagement
• Serve as the primary point of accountability for AI execution within Consumer & Business Banking

AI Transformation Director

• Designing user experiences that enhance interaction between humans and AI systems
• Collaborating with cross-functional teams to develop innovative software solutions
• Conducting user research and usability testing to inform design decisions
• Creating user personas and journey maps to guide design development
• Utilizing human-centered design principles to improve product usability
• Analyzing industry trends to incorporate emerging technologies into design strategies
• Developing user interface prototypes to visualize design concepts
• Applying analytical thinking to solve complex design challenges
• Gathering and interpreting user feedback to refine design solutions
• Building meaningful client relationships to understand and anticipate their needs

Senior Human-AI Interaction Designer

• Develops and maintains Asurint’s enterprise AI strategy, roadmap, operating model, governance framework, and implementation priorities in alignment with corporate objectives and business needs.
• Partners closely with leaders across Operations, Product, Technology, Compliance, Legal, HR, Finance, Client Success, and Executive Leadership to identify business challenges and translate them into practical, AI-enabled solutions.
• Builds and manages an AI opportunity pipeline by identifying, evaluating, and prioritizing high-value use cases across the organization.
• Leads enterprise AI initiatives from concept through deployment, including opportunity assessment, requirements gathering, business case development, pilot execution, implementation planning, change management, adoption, and optimization.
• Serves as the organization’s AI subject matter expert, maintaining deep knowledge of generative AI, large language models, workflow automation, AI agents, intelligent search, knowledge management, adoption, and optimization.
• Designs, prototypes, configures, and deploys AI-enabled solutions including copilots, workflow automations, knowledge assistants, decision-support tools, document intelligence solutions, and other business productivity applications.
• Evaluates build-versus-buy options and recommends AI platforms, technologies, and solutions based on business value, scalability, security requirements, integration capabilities, implementation complexity, and return on investment.
• Establishes a structured intake, evaluation, prioritization, and governance process for AI-related requests and opportunities across the enterprise.
• Drives adoption and business utilization of AI solutions through training programs, user enablement, communication strategies, best practices, and organizational change management initiatives.
• Partners with Technology, Security, Compliance, Legal, and Data Governance stakeholders to ensure AI solutions meet organizational and AI governance standards related to responsible AI usage, data privacy, human oversight, risk management, monitoring, approval workflows, and compliance requirements as well as applicable regulatory obligations for sensitive and regulated data.
• Develops success metrics, operational KPIs, and value realization frameworks to measure productivity improvements, operational efficiencies, cost savings, quality enhancements, risk reduction, and business impact.
• Monitors AI initiative performance, user adoption, business outcomes, and return on investment; continuously refines solutions and priorities based on measurable results.
• Facilitates discovery sessions, operational reviews, workshops, and working sessions to identify workflow inefficiencies, automation opportunities, and AI use cases.
• Builds and maintains a portfolio and pipeline of AI opportunities across the organization, balancing quick wins with strategic transformation initiatives.
• Creates reusable AI frameworks, standards, templates, implementation methodologies, and best practices to accelerate enterprise adoption and scalability.
• Serves as a trusted advisor to executive leadership regarding AI strategy, organizational readiness, technology investments, implementation risks, governance considerations, and emerging industry developments.
• Prepares executive-level presentations, strategic recommendations, implementation roadmaps, business cases, performance reporting, and status updates related to enterprise AI initiatives.
• Fosters a culture of innovation, experimentation, operational excellence, continuous improvement, and responsible AI adoption throughout the organization.
• Other duties as required.

AI Product Strategy – Transformation Director

• Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies to ensure shared understanding, semantic consistency, and discoverability of data and knowledge assets.
• Design and evolve information and semantic models that make enterprise data AI‑ready, supporting use cases ranging from traditional analytics and BI to applied machine learning and LLM‑based experiences (e.g., search, retrieval‑augmented generation, and copilots).
• Operationalize data models, taxonomies, and semantic structures through the Enterprise Data Catalog (Alation).
• Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures to ensure consistency and interoperability across business domains and downstream consumption patterns.
• Provide authoritative guidance on semantic conflicts—resolve definition discrepancies, harmonize terms, and mediate cross‑domain dependencies to establish trusted, reusable business meaning.
• Contribute to the enterprise data product framework by defining domain boundaries, shared dimensions, and semantic contracts that enable cross‑domain interoperability and AI consumption.
• Confirm and document prioritized metadata elements for key business processes, analytical use cases, and AI‑enabled workflows, ensuring alignment with governance standards and risk expectations.
• Identify simplification opportunities—reduce redundancy, converge overlapping datasets, and promote canonical sources to improve trust, efficiency, and reusability across analytics and AI platforms.
• Partner with analytics, data science, and AI engineering teams to ensure information architecture, metadata, and semantic context are sufficient to support explainable, governed, and trustworthy AI outcomes.
• Serve as a thought partner, provide insights from modeling, catalog adoption, and AI enablement to shape governance strategy and roadmaps.

• 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 execution of the enterprise AI enablement strategy, translating OhioHealth priorities and the broader Technology and Digital roadmap into operating plans, priorities, and measurable outcomes
• Direct operational execution of prioritized AI initiatives across clinical and operational settings to achieve adoption, workflow integration, and measurable business results
• Establish and maintain enterprise operating standards for how AI initiatives are identified, prioritized, governed, adopted, and measured
• Provide leadership and coordination across distributed AI and analytics leaders in service lines and functions to ensure alignment with enterprise standards, priorities, and adoption expectations
• Serve as the enterprise coordination point between use-case demand and technical delivery, shaping sequencing, readiness, and adoption plans that support system priorities

Senior Director – Enterprise AI Enablement

• Set the Digital & AI direction for the Service Line
• Create an Architecture + Urbanismspecific digital & AI strategy in the context of our 3yr-out vision and strategy of the Architecture + Urbanism, and the strategic priorities of Industries & Sectors.
• Define and regularly update “digital must-win” areas by conducting competitor analyses and gap analysis within existing portfolio of tools and digital products and partnerships.
• Identify which Architecture + Urbanism delivery domains and workflows must be redesigned.
• Setup collaboration rhythm with Digital Intelligence, Investment governance, pipeline management approach and prioritization framework, change network, CoPs, etc.
• Set clear objectives for the transformation that link to overall Architecture + Urbanism performance metrics.
• Own the Opportunity Portfolio
• Collect and pro-actively source digital opportunities and use cases within the organization, in close collaboration with peers in other Service Lines and Industries.
• Kick-start and actively participate in AI studios around the most promising opportunities, to quickly validate and potentially prototype, ideally in real client settings.
• Work closely together with Digital Intelligence counterparts to make buy/build/partner decisions, as well as start/continue/stop decisions, following pre-set guidelines.
• Actively stop or kill initiatives that do not demonstrate clear value, adoption potential, or strategic fit.
• Participate regularly in client conversations to better understand client needs.
• Act as primary interface and product sponsor to product managers, e.g., help get funding, set requirements, mobilize business SME involvement, anything needed to deliver at pace.
• Rewire Service Delivery workflows
• Redesign end-to-end Architecture + Urbanism delivery workflows to embed digital and AI where they materially improve outcomes.
• Work with Service Line leadership to support adjustments to new ways of working.
• Embed Digital & AI in our capabilities and drive adoption
• Build a local network of digital & AI champions (change agents and catalysts) within each Service Area Group.
• Strengthen foundational digital skills and AI usage within the organization (e.g., Drive Citizen Development participation, measure and steer on AI usage, make part of SPO)
• Setup adoption campaigns around new tooling / digital products, and ways of working, incl. training programs and updated global procedures.
• Strengthen data foundations and other boundary conditions
• Turn global data strategy into an actionable plan within the service line, with clear focus around the priority areas (digital must-wins).
• Create knowledge and data libraries around discipline areas, managed within Communities of Practice.
• Setup data governance (who collects, who structures and maintains) and measure adherence and progress.
• Define any other pre-requisites for digital innovation and bake into transformation plan.
• Own the Architecture + Urbanism Digital and AI innovation backlog and roadmap, in partnership with Digital Intelligence, ensuring alignment to strategic priorities and measurable value delivery.
• Drive investment prioritisation and portfolio transparency within the Innovation governance framework, enabling clear decision-making and optimal allocation of resources.
• Champion digital adoption across the Architecture + Urbanism workforce and project delivery, working closely with Services leadership to embed tools, behaviours, and ways of working that maximise impact.

Artificial Intelligence jobs in Ohio

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AI Marketing & Communications Specialist – AI Practice

AI Integration Specialist

Staff Vice President – Enterprise Technology Transformation, AI Execution

Proposal Support – Artificial Intelligence

Managing Director, CX AI Delivery

Lead AI Risk Advisor

VP, Enterprise AI Enablement

AI Agent Engineer

AI Agent Engineer

Senior AI Technology Architect

VP – AI Product Strategy

Knowledge Architect

AI Transformation Director

Senior Human-AI Interaction Designer

AI Product Strategy – Transformation Director

Knowledge Architect

VP of AI, ML and Data Strategy

Senior Artificial Intelligence Engineer

Senior Director – Enterprise AI Enablement

Digital & AI Transformation Director – Architecture, Urbanism