Artificial Intelligence

• Lead a portfolio of applied AI initiatives from opportunity definition and prioritization through technical design, development, production deployment, adoption and continuous improvement
• Establish technical roadmaps, delivery plans, success measures and resource priorities across the portfolio
• Provide technical and delivery leadership across generative AI, agentic AI, machine learning and intelligent automation
• Guide decisions on solution architecture, model and platform selection, data and knowledge architecture, orchestration, evaluation and production engineering
• Lead, coach and develop multidisciplinary technical teams, including AI engineers and data scientists
• Establish ownership, accountability and resource allocation based on business value, complexity, risk, dependencies and capacity
• Drive reusable enterprise AI platforms, components, services, APIs and architectural patterns
• Lead design and implementation of enterprise-grade AI solutions using large language models, RAG, AI agents, orchestration frameworks and machine learning
• Establish AI evaluation and operational practices including testing, monitoring, observability, performance measurement, reliability engineering and continuous improvement
• Embed data protection, security, privacy, validation, compliance and responsible AI practices throughout the AI lifecycle
• Establish technical standards, reference architectures and development patterns for enterprise AI
• Partner with Product, Digital, Data, Architecture, Security, Quality, Compliance and business teams
• Manage delivery accountability across strategic technology partners, vendors and contingent resources
• Communicate with executive stakeholders
• Provide technical oversight across solution design, engineering, evaluation, testing, deployment, observability, incident response and lifecycle management

Senior Manager, Applied AI

• Define and own the DTFS North America AI analytics vision, strategy and roadmap
• Lead the shift from legacy reporting and visualization to AI-platform-enabled analytics, intelligent dashboards, conversational insight experiences and decision-support capabilities
• Translate business questions into a prioritized portfolio of analytics products, use cases and measurable outcomes
• Partner with IT DSS on architecture, data integration, platform enablement, security, application dependencies, release planning, support and operational sustainability
• Lead the Data Management Domain, including operational data stores, data warehouses, semantic and analytical data models, data pipelines and enterprise reporting foundations
• Ensure analytics products use governed, accurate, timely and well-documented data
• Mature data governance practices with Data Stewards, including standards, metadata, documentation, privacy, retention, access and compliance
• Build and maintain the AI analytics product roadmap and backlog
• Enable diagnostic, predictive and prescriptive analytics
• Adapt analytics capabilities and data foundations to support transformation programs and business-process changes
• Establish product performance measures and adoption feedback loops
• Drive an AI- and data-driven culture through consulting, communication, training, self-service enablement and change management
• Lead, coach and develop the AI Analytics team; allocate talent and capacity
• Manage vendor and partner relationships and ensure cost-effective, supportable solutions
• Represent AI analytics and data-management priorities in leadership, governance and cross-functional forums

Enterprise Analytics AI Manager

• Mentor, train, and coach Interns and Consultants
• Facilitate successful completion of project work plans
• Identify project risks and opportunities to increase efficiency
• Build relationships and communicate with client personnel and professional associates
• Support project scope, work plans, staffing, deliverables, and methodology application under Manager direction
• Help clients translate AI investments into sustained workforce adoption, redesigned work, and measurable business value
• Conduct workforce readiness assessments, stakeholder analyses, and adoption diagnostics
• Design activation campaigns, adoption roadmaps, and champion/super-user networks
• Develop role-based learning journeys, AI Academy content, manager enablement toolkits, and learning-in-the-flow-of-work experiences
• Support future-state organization design, role definition, decision rights, workflow redesign, workforce transformation, and value realization
• Develop KPI frameworks, scorecards, workforce/capacity analyses, cost-benefit assessments, and business cases
• Create executive-ready communications, presentations, and client deliverables
• Evaluate, summarize, organize, and interpret workforce, adoption, and organizational data
• Establish business relationships and communicate AI adoption, workforce, and organizational issues to clients, including executives
• Mentor and oversee teams, review work, coordinate across teams, and motivate team members

Senior Consultant – Business Performance Improvement, People & Change, AI People Enablement

• Own and maintain the integrated multi-year Cyan technical delivery roadmap, linking strategic objectives to capabilities, milestones, releases, dependencies, and measurable outcomes
• Translate product priorities into a sequenced technical delivery plan with defined ownership, commitments, decision points, and release targets
• Maintain a unified view of technical delivery status, risks, dependencies, milestones, and decisions across Cyan and dependent organizations
• Drive identification, escalation, and resolution of cross-functional dependencies, ownership gaps, and sequencing conflicts
• Coordinate technical delivery across a hub-and-spoke operating model spanning AI platforms, shared services, product teams, and enterprise functions
• Align annual strategy, roadmaps, and objectives with PI planning, sprint execution, integration milestones, release plans, and production outcomes
• Establish and manage an operating cadence for cross-workstream integration, executive visibility, milestone readiness, and decision management
• Coordinate pilot, launch, and scale readiness activities across testing, environments, data, observability, security, support, governance, and operational controls
• Ensure prototypes and experiments are transitioned into production delivery plans with clear paths for governance, supportability, scalability, and reuse
• Develop executive communications providing visibility into progress, risks, dependencies, tradeoffs, decisions, and outcomes
• Facilitate decision-making by presenting options, impacts, and recommendations, and maintaining decision records across organizational boundaries
• Partner with enterprise planning, technical delivery, and governance stakeholders to align Cyan execution with broader organizational priorities
• Continuously evolve delivery frameworks, onboarding new workstreams and capabilities while maintaining execution speed and accountability

Artificial Intelligence jobs in North Carolina

Senior Manager, Applied AI

Enterprise Analytics AI Manager

Senior Consultant – Business Performance Improvement, People & Change, AI People Enablement

VP, AI Technical Strategy – Integration