Director Of Ai Engineering For Corporate It
Our Corporate IT Organization is driving the adoption of innovation across Eaton! In the role of Director of AI Engineering for Corporate IT, the individual will manage the development and execution of the enterprise AI strategy, roadmap, and investment priorities, ensuring alignment with the broader organizational objectives. They will lead the creation and implementation of a comprehensive AI strategy that supports the company's vision and goals. Responsibilities include researching emerging AI technologies, assessing their business implications, and advising on strategic investments. They will establish a framework and strategy for the deployment and governance of artificial intelligence and generative AI within the enterprise, including creating a centralized function and guidelines to support business initiatives, and enhancing data science efforts across various domains to foster growth, efficiency, and risk management in line with key corporate priorities.
Key Responsibilities
Strategic Leadership
- Define and execute Eaton's AI strategy for manufacturing, aligning with corporate goals and plant-level priorities.
- Partner with operations, engineering, and supply chain leaders to identify high-impact AI opportunities across production, logistics, and maintenance.
- Lead the adoption of generative AI, computer vision, predictive maintenance, and intelligent automation to optimize manufacturing processes.
AI Engineering & Delivery
Build and lead a high-performing AI engineering team focused on scalable, production-grade solutions for industrial environments.Oversee the full AI / ML lifecycle : data ingestion from OT / IT systems, model development, deployment to edge / cloud, and performance monitoring.Champion MLOps best practices and cloud-native architectures (e.g., Azure ML, AWS SageMaker, Databricks) tailored for manufacturing use cases.Governance & Risk Management
Establish enterprise-wide AI governance, including ethical use, compliance with industrial standards, and risk mitigation.Develop policies and frameworks for responsible AI, model transparency, and bias mitigation in safety-critical environments.Innovation & Enablement
Evaluate emerging AI technologies and vendor partnerships to inform build-vs-buy decisions for manufacturing applications.Drive enterprise-wide education and change management to foster AI literacy and adoption across plants and engineering teams.Represent AI initiatives to executive leadership and the Board, articulating impact on productivity, quality, and cost savings.Qualifications
Basic Qualifications
Bachelor's degree in Engineering and / or Computer Science from an accredited institution.Minimum 10 years of experience in engineering or technology leadership, with a focus on AI, data science, or digital transformation.Minimum 2 years of enterprise IT leadership experience defining and executing AI strategies for a multi-billion-dollar industrial organization.Must be authorized to work in the U.S. without company sponsorship.Preferred Qualifications
Proven success delivering AI-powered solutions at scale in manufacturing or industrial environments.Experience with AI applications such as predictive maintenance, defect detection, process optimization, and supply chain analytics.Deep understanding of AI / ML frameworks (e.g., PyTorch, TensorFlow), industrial data platforms (e.g., OSIsoft PI, Snowflake), and programming languages (Python, SQL).Familiarity with MLOps tools and practices (e.g., MLflow, Kubeflow, CI / CD pipelines) and edge deployment strategies.Strong track record of influencing senior stakeholders and driving enterprise-wide transformation in manufacturing settings.