Artificial Intelligence

• 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.

Knowledge Architect

• 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.

Digital & AI Transformation Director – Architecture, Urbanism

• Partner with IT, product, business, and shared service teams to move AI initiatives from intake through adoption.
• Participate in the AI initiative intake process and help define the criteria initiatives must satisfy to progress through governance gates.
• Help maintain the governance framework for Enterprise AI, including gate criteria, review standards, and decision documentation.
• Help shape the prioritization and intake methodology in partnership with Strategic Technical Product Managers.
• Contribute to the AI portfolio health view delivered to senior leadership — status, risk, and tradeoff reporting that drives executive decisions.
• Help shape the operating model and ways-of-working standards for how AI initiatives move through the enterprise.
• Facilitate cross-functional alignment sessions across IT, business, and shared service partners.
• Continuously improve the operating model and ways of working to scale the AI program with cross-functional partners.
• Escalate risks, dependency conflicts, and stalled initiatives to senior leadership with recommendations on how to create a path forward.

Enterprise AI Programs – Governance Specialist

• Own delivery, performance, and risk outcomes for a large, complex Claims Applied AI portfolio spanning multiple teams, domains, and value streams
• Drive measurable business value across the end-to-end claims journey by developing, testing, deploying, and scaling Predictive, Generative, and Agentic AI solutions
• Be the senior business partner for Claims leaders
• Build deep partnerships within portfolio and value stream frameworks
• Lead and develop senior leaders and teams
• Provide portfolio-level technical direction and oversight
• Ensure disciplined architecture and delivery trade-offs across quality, grounding, latency, cost, scalability, and regulatory risk
• Establish and enforce evaluation, monitoring, and production readiness across solution types
• Set governance expectations for unstructured data and retrieval across Claims
• Accountable for AI governance and compliance-by-design across the Claims portfolio
• Influence technology integration and platform strategy
• Champion reuse and scalability by partnering with AI platform owners and peers
• Provide thought leadership and change leadership
• Oversee portfolio planning, dependencies, resourcing, and financial stewardship

AVP Applied AI, Claims

• Lead a team of product owners and product managers focused on complex end-user experiences and emerging digital commerce capabilities.
• Help lead the development of new digital commerce capabilities from concept through pilot and scale, enabling AI-driven experiences that connect consumers, brands, and financing solutions within emerging commerce platforms.
• Maintain clarity for the team to ensure successful delivery of new and existing digital capabilities and collaborate with stakeholders across technology, platform, and business teams to align product goals.
• Manage the product lifecycle from ideation to launch, helping shape the company's strategy for AI-enabled commerce experiences.

Senior Manager – Product Agentic AI

• Develop and implement AI governance frameworks
• Conduct risk assessments to maintain compliance with firm policies
• Guide the adaptation of AI usage and maintenance protocols
• Monitor changes in the regulatory landscape affecting AI
• Mentor team members on recommended practices in AI governance
• Collaborate with cross-functional teams to enhance program effectiveness
• Evaluate third-party risks associated with AI technologies
• Stay informed on emerging trends in AI and technology

RFM AI Governance Manager

• Define and evolve target-state data platform and data services architecture aligned to business strategy and modernization goals
• Establish enterprise standards and reference architectures for data as a service, event-driven architecture, and API-based data access
• Drive adoption of data as a strategic asset, enabling operational, analytical, and intelligent system use cases across the enterprise
• Architect scalable data platforms that support both traditional workloads and emerging AI/ML use cases, grounded in trusted enterprise data
• Define integration patterns that unify data services, APIs, and AI capabilities to enable intelligent applications and automation
• Enable data accessibility, reuse, and contextualization to support cross-platform consumption, including emerging agent-driven workflows
• Establish foundational patterns for data retrieval, context enrichment, and grounding to support advanced use cases such as AI and real-time decisioning
• Architect and design enterprise-grade data pipelines supporting batch, streaming, and real-time workloads
• Build and standardize data ingestion, transformation, and distribution frameworks that power scalable data services capabilities
• Ensure delivery of high-quality, governed, and trusted data pipelines that support analytics, APIs, and downstream intelligent applications
• Implement best practices for event-driven data movement and microservices-based integration patterns
• Design data models and structures that enable data productization and consumption across analytics, APIs, and AI-driven use cases
• Architect high-performance storage solutions (including Bigtable, Spanner and other GCP services) to meet throughput, latency, and scalability requirements
• Enable secure, governed, and efficient data access patterns across operational, analytical, and real-time environments
• Serve as a trusted advisor and technical leader, mentoring teams, driving best practices, and partnering with stakeholders to identify high-value data and AI-enabled use cases

Senior Data Architect – AI

• Lead end-to-end delivery of business-critical contact center and customer experience technology solutions.
• Own program-level governance for CCaaS engagements including integrated project plans and risk management.
• Provide strong program leadership to cross-functional, globally distributed teams.
• Champion effective communication delivering updates for various internal audiences.
• Drive and govern Agile and hybrid delivery lifecycles for CCaaS implementations.
• Plan and execute structured knowledge transfer and transition-to-sustainment activities.
• Operate within structured release cadences and governance rituals.
• Manage project-level budgets, forecasts, and financials to ensure delivery within approved scope.
• Encourage and lead an engaging team environment that celebrates wins and fosters a sense of shared purpose.
• Show a high degree of agency proactively identifying opportunities.

Manager, Delivery – CX AI

• Lead teams delivering governed Generative AI solutions
• Design testing strategies, evaluation frameworks, and governance controls
• Supervise teams and manage client accounts
• Uphold PwC's values and professional standards

AI Evaluation Engineer, Manager

• Set and execute a bold vision for integrating AI, data science, and automation across all Commercial Banking client and colleague experiences
• Lead cross-functional workstreams across product, technology, marketing, and operations to deliver measurable business outcomes
• Serve as a strategic advisor, identifying emerging technologies and trends that can be leveraged to drive value
• Champion a culture of innovation, agility, and data-driven decision-making across the organization
• Act as a change agent, driving adoption of digital and AI capabilities embedded within business processes and workflows
• Develop and lead the Commercial Bank’s Digital & AI strategy, ensuring alignment with enterprise objectives and client needs
• Identify high-value use cases that drive efficiencies and enhance experiences using automation, AI, and Generative AI across customer and colleague journeys
• Foster strong collaboration with Commercial business leaders and the AI Center of Excellence (COE) to ensure alignment on priorities and outcomes
• Drive execution and delivery of the AI roadmap in partnership with the AI COE and technology partners
• Measure, track, and communicate the business impact of AI initiatives to stakeholders and senior leadership

Executive Director – Digital & AI Transformation

• Responsible for measuring business performance and surfacing actionable quantitative and qualitative insights
• Define, govern and maintain performance frameworks that measure progress against strategic goals
• Establish and manage KPIs, success metrics, and scorecards that reflect outcomes and effectiveness
• Synthesize quantitative data with qualitative inputs to deliver holistic insights
• Design and manage feedback mechanisms like surveys and qualitative interviews
• Evaluate the effectiveness of initiatives and identify opportunities to improve performance
• Serve as a connector between AI enablement, analytics, and business teams to ensure AI insights are scalable

Senior Analyst, AI Business Performance & Insights

• Develop and own the enterprise AI adoption strategy aligned with SupplyHouse's business objectives and long-term growth plans
• Identify high-impact AI use cases across procurement, operations, sales, customer service, and finance, and prioritize based on ROI and feasibility
• Serve as the primary internal authority on enterprise AI tools, platforms, and best practices including large language models, agentic workflows, and AI-powered analytics
• Monitor the AI technology landscape and advise executive leadership on emerging opportunities and risks
• Design and execute enterprise-wide change management programs grounded in proven methodologies to drive sustained, high-quality AI adoption across all levels and functions
• Act as a culture carrier for AI transformation championing a mindset of curiosity, continuous learning, and responsible experimentation throughout the organization
• Build internal champions, AI ambassadors, and center-of-excellence structures to scale AI literacy and usage across every business unit
• Develop training curriculum, playbooks, and role-based enablement programs to upskill employees on AI tools and workflows at every level, from frontline staff to senior leadership
• Create psychological safety around AI adoption by proactively addressing employee concerns about job displacement, skill gaps, and the pace of change positioning AI as a tool that augments human capability rather than replaces it
• Partner closely with the Human Resources team to embed AI competency into hiring profiles, onboarding programs, performance frameworks, and career development pathways
• Lead executive communications, all-hands presentations, and town halls related to AI strategy, adoption milestones, and organizational impact
• Identify and mitigate human-side risks of AI adoption including change fatigue, resistance patterns, and inequitable access to enablement resources across teams
• Partner with department heads across IT, Operations, Human Resources, Legal, and Finance to embed AI into core business processes
• Collaborate with the IT and Data Engineering teams to ensure secure, compliant, and scalable AI infrastructure
• Manage relationships with external AI vendors, consultants, and technology partners
• Coordinate with Legal and Compliance teams to establish responsible AI governance policies, data privacy standards, and risk frameworks
• Define KPIs and success metrics for AI adoption initiatives and report progress to the C-suite and Board as needed
• Establish feedback loops and continuous improvement processes to optimize AI tool performance and user experience
• Build business cases and ROI models to justify AI investments and scale successful pilots enterprise-wide
• Build, lead, and mentor a high-performing team of AI program managers, analysts, and change agents
• Foster a culture of experimentation, curiosity, and responsible innovation within the team and across the organization

Director, Enterprise AI Adoption

• Conduct structured discovery with functional teams (front desk, call center, medical assistants, clinical operations, billing, HR) to surface high-friction, high-volume manual processes.
• Support finance and analytics teams to quantify automation opportunity value — time savings, error reduction, cost avoidance, patient/staff experience improvement.
• Evaluate build vs. buy vs. configure for each opportunity, with a bias toward in-house development using available platforms.
• Maintain an ongoing opportunity pipeline to ensure the organization is continuously identifying new areas for improvement.
• Develop and maintain a rolling automation and AI roadmap, ranked by impact, feasibility, and strategic alignment.
• Present prioritized roadmaps to the executive sponsor with supporting business cases and resource requirements.
• Manage tradeoffs between quick wins and longer-horizon investments, balancing speed of value delivery with solution durability.
• Support finance and analytics teams track and report on ROI and outcome metrics for deployed solutions.
• Serve as a credible, non-technical communicator to the executive team — translating complex AI and automation concepts into clear business implications.
• Build and maintain trusted relationships with department heads and functional leads; act as a collaborative partner, not a top-down implementer.
• Proactively surface risks (vendor dependency, data privacy, regulatory compliance under HIPAA) and recommend mitigation strategies.
• Represent the AI & Automation function in organizational planning discussions and technology governance forums.
• Directly design, build, deploy, and support automation and AI solutions — this is a hands-on role, not purely advisory.
• Leverage available tools, including Microsoft Copilot and Claude AI (Anthropic), as a core development accelerator for natural language processing, document intelligence, workflow generation, and internal tooling.
• Utilize integration platforms, RPA tools, and API-based workflows to connect disparate healthcare software systems (EHR, PM, scheduling, billing, communication platforms).
• Collaborate with IS&T colleagues on infrastructure, security, and data governance requirements for each solution.
• Build solutions with maintainability in mind — document thoroughly and design for handoff or scale as the team grows.
• Assess existing vendor-hosted AI solutions and develop transition plans to migrate appropriate capabilities in-house.
• Evaluate and recommend platforms, tools, and APIs; manage vendor relationships for any retained third-party solutions.
• Monitor the AI and automation vendor landscape for new capabilities relevant to healthcare services operations.

Director of AI – Automation

• Provide strategic leadership and hands-on direction for the design, build, and governance of automation and AI solutions supporting the CTG organization
• Partner closely with CTG technology leaders, risk and governance stakeholders, enterprise architecture, security, data teams, and approved third-party vendors to deliver targeted automation and AI capabilities that improve efficiency, strengthen controls, and enable better decision making across CTG functions
• Accountable for oversight, governance, and driving execution of automation and AI solutions
• Define and lead the automation and AI strategy for the Corporate Technology and Governance organization
• Drive the design and delivery of automation and AI solutions supporting CTG functions
• Establish and maintain CTG‑specific standards, guardrails, and governance for automation and AI
• Oversee end‑to‑end solution delivery, including requirements definition, design, testing, deployment, and ongoing support
• Ensure appropriate controls are embedded in automation and AI solutions
• Coordinate with enterprise technology, risk, security, and data partners to ensure CTG automation and AI solutions comply with policies, standards, and supervisory expectations
• Evaluate platforms, tools, and vendor solutions relevant to CTG automation and AI needs
• Track performance, value realization, and risk indicators for CTG automation and AI initiatives
• Lead, develop, and retain a high‑performing team

IT Director I – Automation and AI

• Learn how teams across the business work (Customer Service, Operations, Merchandising, Marketing, Product, etc.) and identify high-impact opportunities where AI can help
• Partner with stakeholders to define problems clearly, map workflows, and estimate potential value and effort
• Research and evaluate AI tools and approaches (LLMs, copilots, workflow automation, search/RAG, lightweight agents) for business use cases
• Build and test small prototypes or proofs of concept (e.g.: prompt workflows, chat-based assistants, automation scripts, internal knowledge helpers)
• Create clear documentation and playbooks so others can reuse what you build (prompt guides, best practices, example workflows)
• Help run simple enablement activities like demos, office hours, training sessions, and collecting feedback
• Track results and learnings, including what worked, what did not, and recommendations for next steps
• Follow responsible AI practices, including data privacy, security, and quality standards

AI Enablement Intern

• Develop and maintain core School of Splunk Field Sales Enablement portfolio
• Design and deliver AI-focused onboarding and upskilling curricula
• Integrate critical technical sales skills into curriculum for learners to develop mastery
• Compose test questions, evaluations, and assessments that validate proficiency
• Develop and continuously refresh learning content that reflects the messaging and positioning related to Splunk platform
• Work with key stakeholders to develop technical seller training programs
• Serve as a trusted advisor to technical sales stakeholders and SMEs
• Update and optimize existing GFE training assets to reflect Cisco's current strategic direction

See all jobs on JobTailor