Manager, Aircraft Maintenance Operations, Amazon Air

Key job responsibilities

• Oversee daily maintenance operations workflow, ensuring effective communication and coordination between maintenance providers and network operations
• Manage real-time operational decisions regarding maintenance events, aircraft swaps, and recovery scenarios to minimize network disruption and maintain schedule integrity
• Develop and drive real-time fleet health monitoring strategies and technical readiness assessments for the Amazon Air global fleet
• Drive implementation of AI/ML technologies to enhance operational maintenance strategies, leveraging GenAI tools to synthesize data and surface actionable insights
• Serve as primary contact for maintenance-related communications, developing protocols to manage service impacts and customer experience
• Create data-driven strategies to maximize maintenance On-Time Performance
• Develop and document lessons learned to continually improve maintenance operations across the network
• Champion adoption of approved AI solutions within daily workflows — evaluating emerging tools, leading pilot efforts, and providing feedback that shapes continuous process improvement

Basic Qualifications

• Bachelor's degree
• 5+ years of program or project management experience
• Experience using data and metrics to determine and drive improvements
• Experience owning program strategy, end to end delivery, and communicating results to senior leadership
• 5+ years Airline, military, or equivalent experience with 14CFR 121 operations in line maintenance, maintenance control, heavy maintenance or equivalent
• FAA Part 65 Airframe and Powerplant certificate or equivalent
• Experience with data analytics and technology implementation in aviation

Preferred Qualifications

• Experience using data and metrics to drive actionable insights at scale
• Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
• 5+ years of driving process improvements experience
• Background in aircraft maintenance control and line maintenance operations
• Understanding of machine learning fundamentals and their potential in maintenance forecasting