Director- AI Engineering

Responsibilities include researching emerging AI technologies, assessing their business implications, and advising on strategic investments. Build and lead a high-performing AI engineering team focused on scalable, production-grade solutions for industrial environments. 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. Evaluate emerging AI technologies and vendor partnerships to inform build-vs-buy decisions for manufacturing applications. 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. Bachelor's degree in Engineering and/or Computer Science from an accredited instituition. 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. 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.