Job Description Summary

The Senior Engineer – Fleet Monitoring and AI Enablement is responsible for supporting the installed base through fleet monitoring, diagnostics, issue resolution, outage support, fleet configuration, and maintenance of fleet data. In addition to core fleet monitoring responsibilities, this role will help lead the modernization of monitoring practices by developing and applying digital, analytics, and AI-enabled solutions that improve diagnostic effectiveness, operational efficiency, and fleet performance.

This position requires strong technical judgment, analytical capability, and cross-functional collaboration to identify emerging fleet issues, improve monitoring workflows, and implement scalable solutions that enhance reliability, availability, maintainability, and customer outcomes. The Senior Engineer will serve as a key technical resource and change agent within the team, helping shape the future of fleet monitoring through data-driven insights, automation, standardization, and adoption of advanced analytics and AI tools.

A core part of this role will be to build team capability by training and mentoring team members, sharing best practices, and enabling broader adoption of new tools and methods. The engineer will also help translate AI and digital opportunities into practical applications for fleet monitoring, ensuring the team is equipped to operate at the leading edge of technology and diagnostics.

Job Description

Roles and Responsibilities

• Support the installed base through fleet monitoring and diagnostics, customer issue resolution, outage management, service bulletin implementation, fleet configuration, and fleet data maintenance.
• Monitor fleet performance indicators and operational data to identify emerging issues, recurring trends, and opportunities to improve reliability, availability, and maintenance outcomes.
• Lead root cause investigations and develop data-driven recommendations to resolve fleet and customer issues.
• Drive continuous improvement in fleet monitoring processes, standard work, and team operating rhythms to improve efficiency, consistency, and quality of technical outcomes.
• Identify and implement opportunities to improve data quality, alert effectiveness, prioritization methods, diagnostic workflows, and knowledge management practices.
• Support the development and adoption of digital, analytics, automation, and AI-enabled solutions that improve anomaly detection, issue triage, decision support, knowledge capture, and engineer productivity.
• Partner with engineering, services, digital, and cross-functional teams to define use cases, requirements, and implementation plans for advanced monitoring, analytics, and AI initiatives.
• Contribute to modernization of fleet monitoring capabilities through automation, standardization, and practical application of data, analytics, and AI tools.
• Use engineering judgment and technical expertise to solve complex operational and product-related issues using multiple internal and external sources of information.
• Serve as a technical resource, best-practice leader, and capability builder for the team by sharing knowledge, creating guidance, and supporting development of less experienced colleagues.
• Help train the team on new digital workflows, analytics methods, and AI-assisted monitoring approaches to accelerate adoption and build long-term capability.
• Communicate technical findings, risks, and recommendations clearly to stakeholders across functions and levels of the organization.
• Lead or support projects of moderate scope and complexity related to fleet performance, monitoring effectiveness, process improvement, digital enablement, and AI adoption.
• Help identify opportunities to create or refine tools that improve fleet monitoring efficiency, consistency, and decision quality.

Required Qualifications

• For roles outside of the USA -

  This role requires significant experience in Engineering/Technology, Fleet Management, Monitoring & Diagnostics, Services Engineering, or related technical disciplines. Knowledge level is comparable to a Master’s degree from an accredited university or college (or a high school diploma with relevant experience).

   

Desired Characteristics

• Strong experience in fleet monitoring, diagnostics, reliability, maintenance, or services engineering.
• Demonstrated ability to drive continuous improvement and implement process enhancements in an operational or engineering environment.
• Experience working with digital tools, data analytics, automation, or AI-enabled technologies to improve technical or operational outcomes.
• Demonstrated ability to build, implement, or improve tools, workflows, or decision-support solutions.
• Strong analytical and problem-solving skills with demonstrated ability to analyze and resolve complex issues.
• Strong oral and written communication skills.
• Strong interpersonal skills with the ability to collaborate across functions and influence without direct authority.
• Demonstrated ability to lead projects and execute on improvement initiatives.
• Ability to coach, train, and develop others in new processes, tools, and technologies.
• Familiarity with data quality management, monitoring logic, alerting strategies, and performance metrics.
• Ability to document, plan, and execute programs and process improvements effectively.
• Established project management skills.

Note:

To comply with US immigration and other legal requirements, it is necessary to specify the minimum number of years' experience required for any role based within the USA. For roles outside of the USA, to ensure compliance with applicable legislation, the JDs should focus on the substantive level of experience required for the role and a minimum number of years should NOT be used.

Additional Information

#LI-Remote - This is a remote position