Artificial Intelligence & Digital Transformation Manager

Quanex•Piney Point Village, TX

6d•$140,000 - $170,000•Hybrid

About The Position

The Digital Transformation and Artificial Intelligence Manager will be responsible for developing, governing, and leading enterprise digital transformation and artificial intelligence strategies for Quanex, with a focus on organizational-level change, practical implementation, and measurable business outcomes across manufacturing operations, corporate functions, and core business processes.

Requirements

Bachelor's degree in Computer Science, Data Science, Information Systems, Engineering, Business Analytics, Operations Management, or a related field required; Master's degree preferred.
Minimum of 10 years of relevant professional experience, including:
7+ years in information technology, data analytics, digital transformation, manufacturing technology, enterprise applications, or related business technology functions.
5+ years leading complex technology, automation, analytics, or transformation initiatives across multiple business areas.
3+ years directly supporting AI, advanced analytics, automation, or digital transformation programs.
2+ years leading teams, programs, or cross-functional initiatives.
Demonstrated success implementing AI, machine learning, automation, advanced analytics, or data-driven solutions within manufacturing environments.
Experience with manufacturing systems and processes such as ERP, MES, quality systems, maintenance systems, supply chain systems, production planning, and plant operations preferred.
Strong understanding of AI technologies, including generative AI, machine learning, natural language processing, predictive analytics, computer vision, automation, data governance, and model lifecycle management.
Proven ability to build business cases, develop technology roadmaps, establish governance models, and deliver executive-level reporting.
Experience leading organizational change management programs, including stakeholder engagement, communication planning, training, adoption strategy, and sustainment.
Strong business acumen with the ability to influence executive leadership, plant leadership, and cross-functional stakeholders.
Excellent communication, analytical, and problem-solving skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
Knowledge of responsible AI principles, cybersecurity, data privacy, compliance, and risk management practices.
Ability to manage multiple priorities, vendors, initiatives, and stakeholders within a fast-paced manufacturing environment.

Nice To Haves

Professional certifications in AI, machine learning, data analytics, project management, change management, or AI governance are preferred.

Responsibilities

Develop and lead the company's enterprise AI strategy, roadmap, governance framework, and adoption initiatives.
Identify, prioritize, and implement AI and digital transformation opportunities that improve operational efficiency, quality, safety, customer experience, forecasting, and decision-making.
Partner with business, manufacturing, and IT leaders to translate operational challenges into practical, scalable technology solutions.
Lead AI initiatives across manufacturing operations, including production planning, predictive maintenance, quality inspection, computer vision, process optimization, supply chain management, inventory optimization, and shop floor productivity.
Establish policies, standards, and governance processes that ensure the responsible, secure, ethical, and compliant use of AI technologies.
Assess and prioritize AI opportunities based on business value, technical feasibility, risk, data readiness, implementation complexity, and return on investment.
Oversee AI pilots, proofs of concept, vendor evaluations, solution selection, implementation planning, deployment, and ongoing support models.
Lead enterprise automation and business enablement initiatives that improve efficiency, strengthen controls, and reduce manual processes.
Drive organizational change management efforts, including stakeholder engagement, communications, training, adoption measurement, and long-term sustainment.
Collaborate with cybersecurity, legal, compliance, HR, audit, data, infrastructure, and architecture teams to identify and mitigate AI-related risks.
Measure and communicate program success through key performance indicators such as productivity improvements, cost savings, quality enhancements, risk reduction, and employee adoption.
Monitor emerging AI technologies, industry trends, regulations, and manufacturing best practices to keep the organization competitive and forward-looking.
Provide leadership, coaching, and direction to internal teams, business stakeholders, vendors, and implementation partners.