Director Artificial Intelligence

Job Summary The Director of AI is a business-facing, hands-on leader responsible for embedding AI into day-to-day operations across the MCT division. This role focuses on identifying opportunities with business teams, rapidly delivering working solutions, and scaling what works. The ideal candidate is equally comfortable in executive discussions and hands-on technical delivery. Key Responsibilities
Opportunity Discovery & Value Creation Work directly with business units to identify, qualify, and prioritize AI opportunities.
Build business cases, define KPIs, and demonstrate measurable value through pilots and production deployments.
Establish a demand intake and prioritization framework for AI initiatives and manage the portfolio based on results AI Solution Delivery Lead rapid experimentation and proof-of-value initiatives; fail fast and iterate.
Lead early-stage AI implementations end-to-end, serving as the subject matter expert and technical escalation point from POC through pilot and initial production rollout Growth, Commercial Enablement & Operational Impact Identify and prioritize AI-enabled revenue growth opportunities (pricing optimization, product differentiation, digital services, installed base monetization).
Partner with commercial, product, and service leaders to embed AI into customer-facing workflows and offerings.
Lead deployment of AI-enabled workflow automation and process redesign across operations and SG&A
Reduce cycle time, scrap, rework, inventory, and administrative inefficiencies through applied AI and automation
Standardize and scale proven AI use cases across business units, ensuring adoption translates into sustained operating discipline and measurable result Change Management & Adoption Act as a change agent, helping business teams adopt AI-driven ways of working.
Educate stakeholders on AI capabilities, limitations, and best practices. Governance & Scale Ensure solutions comply with enterprise security, privacy, and responsible AI standards.
Standardize architectures, tools, and MLOps for scalable solutions. Qualifications A Bachelor's degree in computer science, data science, information management, or a related technical field, Master's degree preferred
Minimum 7 years of experience in enterprise technology with a strong background in cloud data platforms, automation platforms, or ERP
Exposure to industrial, manufacturing, or engineered product environments preferred
Experience operating within enterprise governance frameworks.
At least 3 years focused on applied AI or GenAI, with experience delivering solutions in real business workflows.
Experience with modern AI platforms and LLM architectures, including RAG, MCP, and enterprise grounding patterns
Self-driven, cross-functional leader with the ability to drive change and adoption across teams.
Strong business acumen and ability to articulate value in non-technical terms.