Sr. Director, Enterprise Artificial Intelligence

Main Job Responsibilities / Competencies

The Director, Enterprise Artificial Intelligence is responsible for leading the Company's enterprise Artificial Intelligence (AI) strategy and driving business transformation through the adoption of AI-enabled capabilities across the organization. This role partners closely with Executive Leadership, Manufacturing, Supply Chain, Engineering, Quality Assurance, Regulatory Affairs, Commercial Operations, Finance, Human Resources, Cybersecurity, Infrastructure, and Information Technology to identify, prioritize, and implement Artificial Intelligence solutions that improve operational efficiency, decision making, customer experience, innovation, and long-term competitive advantage.

This position provides strategic leadership for enterprise AI governance, Responsible AI, Generative AI, Agentic AI, Machine Learning, Intelligent Automation, and enterprise knowledge management while ensuring AI initiatives deliver measurable business value, align with corporate objectives, and support secure, scalable, and sustainable business transformation.

Lead and execute the Company's enterprise Artificial Intelligence strategy aligned with corporate objectives, digital transformation initiatives, and measurable business outcomes.
Establish and operationalize an Enterprise AI Center of Excellence (AI CoE) responsible for governance, standards, reusable AI capabilities, and enterprise adoption.
Drive enterprise business transformation through the application of Artificial Intelligence, Generative AI, Agentic AI, Machine Learning, Predictive Analytics, and Intelligent Automation.
Partner with executive leadership and business stakeholders to identify and prioritize AI initiatives that improve operational efficiency, product quality, customer experience, revenue growth, and employee productivity.
Develop enterprise AI roadmaps, investment strategies, business cases, and value realization plans.
Establish Responsible AI governance, AI policies, model lifecycle management, and AI risk management practices.
Lead implementation of RAG, semantic search, vector databases, AI assistants, and enterprise knowledge management.
Integrate AI with Oracle Fusion ERP, OCI, OIC, Salesforce, MES, PLM, enterprise data platforms, and cloud-native applications.
Establish KPIs and executive dashboards measuring AI adoption and business value.
Lead organizational change management and enterprise AI adoption.
Recruit and mentor a team of AI/Business Engineers, Data Engineer/architects and AI Product Owner.
Evaluate emerging AI technologies and strategic technology partnerships.
Foster innovation, continuous improvement, and responsible AI adoption.
Other duties as assigned.

Requirements

EDUCATION & TRAINING

Bachelor’s degree in computer science, Artificial Intelligence, Data Science, Engineering, Information Technology, Business Administration, or related discipline required or equivalent combination of education/experience.
Advanced degree preferred.
Professional certifications in AI, Cloud Computing, Enterprise Architecture, Cybersecurity, Project Management, or Data Analytics are highly desirable.

Experience

12+ years of progressive leadership experience in enterprise technology, digital transformation, Artificial Intelligence, data analytics, enterprise architecture, software engineering, or related disciplines.
3+ years leading enterprise digital AI transformation organizations.
Demonstrated success developing enterprise AI strategies delivering measurable business transformation.
Experience with Generative AI, LLMs, Agentic AI, RAG, Machine Learning, Predictive Analytics, and Intelligent Automation.
Experience in integrating AI with ERP, CRM, Supply Chain, Manufacturing, Finance, HR, and enterprise platforms.
Experience presenting AI strategies and business outcomes to executive leadership and Boards.
Enterprise AI governance, organizational change management, and global business transformation.
FDA-regulated medical devices, biotechnology, pharmaceutical, life sciences, or other regulated industries preferred.

Skills

Strong knowledge of enterprise Artificial Intelligence strategy, governance, operating models, enterprise architecture, and business transformation methodologies, including the development of AI roadmaps, investment strategies, Centers of Excellence, and enterprise adoption frameworks.
Deep understanding of Generative AI, Large Language Models (LLMs), Agentic AI, Retrieval-Augmented Generation (RAG), prompt engineering, AI orchestration frameworks, semantic search, vector databases, AI assistants, autonomous agents, and intelligent automation technologies.
Strong understanding of Machine Learning, Predictive Analytics, Natural Language Processing (NLP), Computer Vision, AI model lifecycle management, model evaluation, MLOps, LLMOps, and enterprise AI platform operations.
Strong knowledge of enterprise cloud platforms including Oracle Cloud Infrastructure (OCI), Microsoft Azure, Amazon Web Services (AWS), Google Cloud Platform (GCP), cloud-native architectures, APIs, microservices, enterprise integration, event-driven architectures, and hybrid cloud environments.
Deep understanding of enterprise data architecture, data governance, master data management, metadata management, data quality, knowledge management, vector storage, and enterprise information management principles supporting AI-enabled decision making.
Strong understanding of Responsible AI principles, AI governance, cybersecurity, privacy, regulatory compliance, intellectual property protection, model transparency, explainability, AI ethics, enterprise risk management, and secure AI deployment practices.
Demonstrated ability to align Artificial Intelligence investments with corporate strategy by developing business cases, value realization frameworks, key performance indicators (KPIs), executive dashboards, and measurable financial and operational outcomes.
Ability to partner effectively with Executive