Define and execute the organization's enterprise AI vision, strategy, and operating model.
Develop a multi-year roadmap for AI adoption, platform investments, business enablement, and technology modernization.
Establish governance, funding, prioritization, and success metrics for AI initiatives.
Build and manage a balanced portfolio of AI programs that drive business value while maintaining appropriate operational, security, and risk controls.
Evaluate emerging technologies and identify opportunities to improve business performance, customer experiences, operational efficiency, and employee productivity.
Serve as a trusted advisor to executive leadership on AI strategy, opportunities, risks, and industry trends.
Lead the development of enterprise AI platform capabilities that support scalable, secure, and reusable AI solutions.
Define architectural standards for intelligent applications, automation platforms, digital assistants, enterprise knowledge solutions, and AI-enabled workflows.
Establish foundational capabilities supporting:
Model access and orchestration
Knowledge retrieval and search
Enterprise data integration
Monitoring and observability
Security and governance controls
Drive adoption of AI-assisted software development practices across the software delivery lifecycle.
Partner with architecture, engineering, infrastructure, operations, security, and data teams to modernize technology delivery through AI-enabled capabilities.
Collaborate with business leaders to identify and prioritize high-value AI use cases.
Lead initiatives focused on:
Intelligent automation
Decision support systems
Document and knowledge management
Workflow optimization
Productivity enhancement
Customer and employee experience improvements
Develop frameworks for evaluating, prioritizing, and scaling AI opportunities across the organization.
Establish adoption strategies, change management programs, and success measurements for enterprise AI initiatives.
Build organizational AI literacy through education, enablement programs, and communities of practice.
Partner with risk, security, legal, compliance, and data governance stakeholders to ensure responsible AI adoption.
Embed security, privacy, transparency, human oversight, and operational controls into AI platforms and business solutions.
Support the development and operationalization of enterprise AI governance frameworks.
Balance innovation and experimentation with appropriate governance and risk management practices.
Promote ethical and responsible use of AI technologies across the organization.
Lead delivery of enterprise AI initiatives from strategy through implementation and adoption.
Establish delivery frameworks, operating models, and performance measures that ensure successful execution.
Manage technology investments, budgets, vendor relationships, and strategic partnerships.
Drive accountability for scope, timelines, quality, adoption, and business outcomes.
Ensure AI initiatives are scalable, supportable, and aligned with enterprise architecture and operational standards.
Build and lead a high-performing team of AI, engineering, architecture, automation, and technology professionals.
Foster a culture of innovation, experimentation, accountability, and continuous learning.
Mentor leaders and technical teams while establishing clear goals, priorities, and performance expectations.
Serve as a catalyst for organizational change and technology transformation.
Promote collaboration across business and technology functions to accelerate enterprise adoption.
Qualifications
15+ years of progressive leadership experience in technology, digital transformation, software engineering, architecture, data, automation, or emerging technologies.
Significant experience leading enterprise-scale AI, automation, analytics, or digital transformation initiatives.
Demonstrated success building and executing technology strategies that deliver measurable business outcomes.
Experience operating within highly regulated or complex enterprise environments preferred.
Strong understanding of modern AI and Generative AI technologies, including:
Large language models and foundation models
AI orchestration and workflow automation
Retrieval and knowledge-based architectures
Prompt engineering and evaluation methodologies
AI application development patterns
Experience with intelligent automation, AI-enabled software development, and enterprise AI platforms.
Familiarity with responsible AI principles, governance frameworks, model lifecycle management, and operational monitoring.
Strong technical foundation across cloud platforms, APIs, distributed systems, data architecture, cybersecurity, identity, and modern engineering practices.
Proven ability to align technology investments with strategic business objectives.
Strong executive communication and stakeholder management skills.
Experience influencing senior leadership and driving enterprise-wide change initiatives.