AI Work Design & Architecture Executive Leader

GE Aerospace; Cheyenne (WY); Remote; USD 200,000 - 300,000; Full time

Benefits offered by this job

Relocation assistance

Remote-friendly

Excellent benefits

Job summary

GE Aerospace is seeking an Executive Leader for AI Work Design & Architecture to guide the enterprise on how AI will intersect with jobs, tasks and skills. You will lead heatmaps of AI impact across the organization and collaborate with HR, data and technology leaders to design future work.

Reporting to the Head of AI Workforce Strategy & Capability, you will shape enterprise taxonomy, career pathways for AI redeployment, and the organizational design required to scale AI-enabled work.

Qualifications

• 12+ years across job architecture and workforce strategy
• Experience with job taxonomy design and task-level work decomposition
• Ability to present executive-ready narratives
• Knowledge of talent market intelligence and its enterprise use
• Experience collaborating with HR, tech, and business leaders in large orgs
• Experience leading a team of senior professionals

Responsibilities

• Lead AI work composition projections and heatmaps of jobs across the enterprise
• Lead the AI capability demand forecast and skills alignment
• Own the Foundational Job Taxonomy and governance across enterprise
• Create enterprise career pathways for AI redeployment
• Partner on organizational design for AI-driven role changes

Skills

Work design

Organizational design

Stakeholder management

Executive communication

Future of work

AI workforce strategy

Talent market intelligence

Cross-functional leadership

Education

Bachelor's degree

Job description

GE Aerospace is seeking an Executive Leader for AI Work Design & Architecture to guide the enterprise on how AI will intersect with jobs, tasks and skills. You will lead heatmaps of AI impact across the organization and collaborate with HR, data and technology leaders to design future work.

Reporting to the Head of AI Workforce Strategy & Capability, you will shape enterprise taxonomy, career pathways for AI redeployment, and the organizational design required to scale AI-enabled work.