Director, AI Solutions & Delivery

Hyperion Materials & Technologies•Dublin, OH

1d•Hybrid

About The Position

The Director, AI Solutions & Delivery leads Hyperion’s enterprise AI portfolio, ensuring AI initiatives align with business priorities and deliver measurable value. This role oversees AI governance, solution architecture, technology selection, and delivery, while guiding teams responsible for AI engineering, platform administration, and solution implementation. The Director drives the secure, scalable, and effective adoption of AI capabilities, enabling business impact, operational efficiency, and long-term value realization. This position will be a hybrid position based in our Dublin, OH office.

Requirements

Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field (Master’s preferred).
10+ years of experience leading technology, analytics, digital transformation, or enterprise application initiatives.
5+ years leading solution architecture, product delivery, or enterprise technology programs.
3+ years of experience designing and implementing AI, machine learning, or generative AI solutions.
Experience building and managing technology portfolios and investment roadmaps.
Proven experience leading cross-functional teams and enterprise initiatives.
Experience translating business strategy into technology solutions.
Demonstrated success managing technical delivery teams.
Direct experience deploying ChatGPT, Claude, or similar enterprise generative AI platforms.

Nice To Haves

Master’s degree

Responsibilities

Establish and manage the enterprise AI intake and evaluation framework.
Build and maintain a centralized inventory of AI opportunities and use cases.
Develop prioritization methodologies based on business value, feasibility, risk, and strategic alignment.
Partner with business leaders to identify opportunities for AI-driven transformation.
Create and maintain the enterprise AI roadmap.
Track value realization and business outcomes across the AI portfolio.
Present portfolio recommendations and investment priorities to executive leadership.
Lead assessment of business problems and determine the most appropriate AI solution approach.
Evaluate and recommend AI technologies, platforms, models, and vendors.
Translate business requirements into scalable AI solution architectures.
Define enterprise standards for Generative AI, Agentic AI, Machine Learning, Intelligent Automation, Knowledge Management, and AI-enabled workflows.
Own end-to-end delivery of enterprise AI initiatives.
Lead AI solution planning, execution, and implementation activities.
Ensure AI projects meet business objectives, timelines, budgets, and quality standards.
Define delivery methodologies and lifecycle processes for AI projects.
Establish repeatable frameworks for scaling AI solutions across business functions.
Lead and develop AI Engineers, Solution Architects, and AI Platform Administrators.
Establish engineering standards and development practices.
Oversee enterprise AI platform operations and governance.
Ensure secure and scalable deployment of AI technologies.
Partner with Information Security and Legal to ensure AI deployments meet security, privacy, and regulatory requirements.
Partner with Information Security & Legal to establish enterprise standards and governance processes for AI solutions.
Ensure AI solutions comply with security, privacy, legal, and regulatory requirements.
Define responsible AI principles and implementation standards.
Lead AI architecture review and governance boards.
Assess technical and operational risks associated with AI initiatives.
Implement controls for monitoring, auditing, and managing AI solutions.
Assess and mitigate AI-related risks, including data leakage, IP exposure, and model misuse.
Evaluate emerging AI technologies and market offerings.
Manage relationships with AI vendors and strategic partners.
Assess platform capabilities and roadmap alignment.
Support licensing, budgeting, and investment decisions.
Develop technology recommendations for future AI capabilities.
Define KPIs to measure AI adoption, value realization, productivity impact, and risk.
Monitor usage trends and performance, iterating on configuration and strategy.
Stay current with emerging generative AI technologies and assess their applicability to the organization.