SUMMARY:
Reporting to SVP, Component Services, this role will lead operational excellence initiatives across our Components sites. This individual will drive continuous improvement by combining Lean Six Sigma methodologies with advanced AI, machine learning, and automation technologies to enhance quality, performance, and efficiency throughout the division. This role will serve as a key partner to site leadership, functional teams, and the executive leadership team in shaping and sustaining a culture of innovation and process optimization. Other key responsibilities include:
 

ESSENTIAL DUTIES AND RESPONSIBILITIES:

         Strategic CI Leadership: Develop and deploy a continuous improvement roadmap tailored to the Components Division’s operational goals, integrating both Lean Six Sigma and AI/automation tools.

         AI Integration: Identify and lead AI-enabled initiatives that improve operational workflows, including predictive analytics, intelligent automation, demand forecasting, inventory optimization, and quality control enhancements.

         Site-Level Collaboration: Partner with plant GMs, HR leaders, quality, engineering, and supply chain teams at U.S. and international locations (e.g., Amsterdam and Thailand) to drive site-specific process improvements and support scalable best practices.

         Project Portfolio Management: Lead and oversee high-impact Kaizen events and cross-functional CI projects. Monitor project outcomes and ROI, ensuring alignment with divisional KPIs and corporate objectives.

         CI Culture Building: Act as a change champion by coaching site teams, mentoring Green and Black Belts, and facilitating workshops to foster CI and AI fluency at all levels of the organization.

         Performance Reporting: Establish metrics and dashboards to measure operational excellence, track savings, and assess AI adoption. Deliver insights and updates to senior leadership on a regular basis.

         Digital & Process Innovation: Collaborate with IT, data analytics, and engineering teams to evaluate and implement smart technologies such as RPA, predictive maintenance, and AI-enhanced visual inspections.

         Capability Development: Design and deliver internal CI and AI training programs to upskill employees, build organizational capacity, and support AAR’s long-term innovation goals.

QUALIFICATIONS:

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the education, knowledge, skill, and/or ability required.

·         Bachelor’s degree in Engineering, Operations, Business, or related field (Master’s preferred)

·         6 years of experience in operations, CI, or process improvement roles, ideally in aviation or aerospace

·         Experience integrating AI, ML, or automation in industrial or operational settings

·         Demonstrated success leading multi-site or international CI initiatives

·         Familiarity with maintenance, repair, and overhaul (MRO) processes and FAA regulations is a plus

·         Proficient in analytics and process improvement tools (e.g., Power BI, Tableau, Minitab, Python, etc.)

·         Strong leadership, communication, and change management skills

·         Preferred hands-on experience with ERP systems and digital transformation projects

·        Working knowledge of AI use cases such as computer vision, NLP, or intelligent workflow automation

PHYSICAL DEMANDS/WORK ENVIRONMENT
The physical demands and work environment characteristics described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the employee is regularly required to sit, stand, bend, reach and move about the facility. The environmental characteristic for this position is an office setting. Candidates should be able to adapt to a traditional business environment.