Sr. Director, AI Center of Excellence

Lincoln Electric

3d•Remote

About The Position

Lincoln Electric is a high-performance industrial machinery and technology leader who helps customers manufacture and maintain vital equipment and infrastructure. Lincoln Electric’s innovative solutions enable higher quality and productivity across a variety of processes including welding, cutting, brazing, machining, process automation, and field repair. The Company leverages proprietary technologies and expertise in materials science, power electronics, automation, and intelligent software to help customers build better and achieve resilience in their operations. Headquartered in Cleveland, Ohio, Lincoln Electric is the essential ‘Linc’ that keeps the economy running. The Company operates 71 manufacturing and automation facilities across 20 countries and serves customers in over 160 countries. For more information about Lincoln Electric and its products and services, visit the Company’s website at https://www.lincolnelectric.com. Position Summary Senior Director, AI Center of Excellence is responsible for leading the company's enterprise AI strategy, governance, adoption, and capability development efforts. This leader will establish and scale a centralized AI Center of Excellence that accelerates responsible workforce adoption of approved AI tools, embeds governance-by-design into everyday work, creates reusable enterprise assets, and prepares the organization to build differentiated AI capabilities powered by proprietary data, institutional knowledge, and manufacturing expertise. As the enterprise AI leader, this individual serves as the connective tissue between business strategy, technology, data, security, legal, privacy, HR, and workforce transformation. The Head of AI CoE will drive measurable business value from AI while ensuring secure, ethical, compliant, and scalable implementation across the enterprise. The ideal candidate is a pragmatic enterprise AI leader who has successfully built or scaled AI adoption in a complex organization, can engage credibly with executives and technical stakeholders alike, and can translate AI opportunities into governed, measurable business outcomes.

Requirements

8-12+ years of leadership experience in AI, data, technology, digital transformation, or enterprise enablement.
Proven success launching and scaling enterprise AI, analytics, automation, or digital transformation programs.
Strong expertise in generative AI, AI governance, data governance, and change management.
Experience leading cross-functional, federated operating models in complex organizations.
Working knowledge of modern AI architectures, including LLMs, agent frameworks, RAG, vector databases, and enterprise AI platforms.
Experience moving AI solutions from experimentation to production while managing risk, security, and governance requirements.
Exceptional executive communication and stakeholder management skills, with the ability to translate AI capabilities into measurable business outcomes.
Manufacturing, industrial, engineering, supply chain, or operations experience strongly preferred.
Experience building organizational AI capabilities through governance frameworks, communities of practice, training, and adoption programs.

Responsibilities

Define and operationalize the AI Center of Excellence charter, operating model, governance structure, executive reporting cadence, and enterprise engagement model.
Establish and communicate the enterprise AI vision, purpose, and North Star, ensuring AI initiatives directly support strategic business priorities and measurable outcomes.
Develop and maintain a multi-year enterprise AI roadmap focused on productivity, innovation, operational excellence, customer value, and competitive differentiation.
Serve as the enterprise advisor to executive leadership on AI opportunities, risks, investments, capabilities, and emerging trends.
Lead enterprise AI maturity planning and readiness initiatives, including workforce, data, technology, and governance capabilities.
Design and implement governance-by-design principles that integrate responsible AI practices into everyday business processes, workflows, and decision-making.
Partner with Security, Legal, Privacy, HR, IT, Data & Analytics, Risk, Compliance, and business leaders to establish enterprise AI policies, standards, controls, and approval processes.
Create scalable frameworks for AI use-case evaluation, risk assessment, solution review, deployment, monitoring, and lifecycle management.
Ensure compliance with evolving AI regulations, privacy requirements, intellectual property protections, and responsible AI standards.
Establish monitoring and oversight mechanisms to manage risks associated with AI, including data leakage, hallucinations, bias, transparency, model drift, and regulatory exposure.
Lead enterprise governance councils and decision forums to balance innovation, speed, risk management, and business value creation.
Accelerate responsible adoption of approved AI tools across the workforce through leadership engagement, executive sponsorship, AI champions networks, and communities of practice.
Develop and scale enterprise AI enablement programs that build AI literacy, capability, and confidence across all levels of the organization.
Create reusable assets including prompt libraries, playbooks, templates, implementation guides, training content, and best-practice repositories.
Foster a culture of responsible experimentation, continuous learning, and knowledge sharing.
Lead change management strategies that support sustainable adoption and maximize the business value of AI investments.
Define and monitor adoption metrics, engagement indicators, and capability-building KPIs to measure organizational progress.
Establish and manage the enterprise AI use-case intake, evaluation, prioritization, funding, and governance process.
Partner with functional and business leaders to identify, assess, and scale high-value AI opportunities.
Develop value realization frameworks that measure productivity improvements, cost savings, revenue growth, quality enhancements, risk reduction, and operational efficiencies.
Maintain visibility into the enterprise AI portfolio, including project status, business impact, dependencies, investment priorities, and governance compliance.
Deliver executive reporting and insights on AI adoption, business outcomes, value realization, and enterprise readiness.
Develop and execute a roadmap for differentiated AI readiness, including enterprise data ownership, knowledge capture, proprietary knowledge enablement, reusable AI patterns, reference architectures, and AI solution architecture maturity.
Establish enterprise knowledge and data foundations required to unlock future AI capabilities built on proprietary organizational expertise, operational practices, engineering know-how, and manufacturing knowledge.
Partner with IT and Data & Analytics leaders to strengthen enterprise AI platforms, architecture, data quality, metadata strategies, and knowledge management capabilities.
Create and maintain reusable AI frameworks, reference architectures, implementation standards, and solution patterns that can be leveraged across business functions.
Evaluate emerging AI technologies and recommend strategic investments that support long-term enterprise competitiveness and differentiation.
Advance organizational maturity in enterprise AI architecture, data governance, and AI-enabled knowledge management.
Build trusted partnerships across manufacturing, engineering, supply chain, operations, product development, service, sales, HR, finance, IT, and corporate functions.
Lead cross-functional steering committees, governance councils, and working teams.
Influence enterprise priorities and decisions in a highly matrixed environment without relying solely on formal authority.
Align stakeholders around common goals, governance standards, adoption objectives, and business outcomes.
Enable collaboration between business and technical teams to accelerate responsible innovation.