AI Manager | Manufacturing Focus

Job Purpose
The AI & Automation Manager will lead the development and implementation of AI-driven solutions across manufacturing and office operations. This role is responsible for identifying automation opportunities, designing practical AI/ML solutions, and deploying scalable tools that improve productivity, accuracy, quality control, and decision-making across the organization.
The ideal candidate is both a strategic thinker and a hands-on technologist, with proven experience applying AI, machine learning, automation, and data solutions in real business or manufacturing environments.
Key Responsibilities
AI Strategy & Roadmap
- Develop and execute the AI and automation roadmap aligned with business priorities.
Identify high-impact use cases across production, quality, supply chain, HR, finance, sales, and back-office operations.
- Translate business problems into practical AI, automation, and data solutions.
- Prioritize AI initiatives based on business impact, feasibility, cost, and implementation timeline.
AI Solution Development & Deployment
- Lead the design, development, testing, deployment, and monitoring of AI/ML models and automation solutions.
- Develop and deploy AI agents or workflow automation tools to reduce manual work, such as report generation, document processing, ERP data analysis, and operational dashboards.
- Apply computer vision solutions for manufacturing use cases such as defect detection, quality inspection, object recognition, and process monitoring.
- Integrate AI solutions with business systems such as ERP, MES, CRM, HR systems, and internal databases.
- Ensure AI models and automation tools are scalable, reliable, and maintainable in production environments.
Data, Governance & Compliance
- Oversee the end-to-end AI model lifecycle, including data collection, model training, validation, deployment, monitoring, and continuous improvement.
- Work with IT and related departments to ensure proper data governance, cybersecurity, access control, and data privacy compliance.
- Establish guidelines for safe and responsible use of AI, including data protection, model outputs, bias, fairness, and ethical considerations.
Cross-functional Collaboration
- Partner with manufacturing, quality, engineering, sales, HR, finance, and IT teams to understand pain points and automation needs.
- Drive user adoption by providing training, communication, and change management support.
- Present AI strategy, progress, business impact, risks, and recommendations to senior leadership.
Team Leadership
- Build, lead, and develop the AI/ML and automation team.
- Coach team members, review technical deliverables, and promote continuous learning.
- Manage vendors, external partners, or consultants when required.