Leader, AI Workforce Intelligence

GE Aerospace; United States; On-site; USD 200,000 - 320,000; Full time

Job summary

GE Aerospace is building a forward-looking AI workforce strategy function to anticipate how work, roles, and skills will evolve with AI. This role leads AI workforce intelligence, connects skills to tasks, and links employee profiles with AI-enhanced capabilities.

You will architect the capability constellation to inform development and investments across the talent ecosystem. Preferred work location is Evendale, OH, with remote options and travel up to 25%.

Qualifications

• 8–12+ years in HR analytics, workforce strategy or related fields.
• Experience designing data architecture and enabling intelligence infrastructure.
• Experience with skills taxonomies and job architecture.
• Proven ability to translate strategy into operating models and governance.
• Strong program and project management in matrix environments.
• Ability to influence stakeholders and collaborate across HR, tech, and business.

Responsibilities

• Lead the establishment of AI workforce intelligence.
• Establish the job and work AI inference foundation at the task level, connected to skills.
• Establish the employee capability AI inference foundation, connecting employee profiles with skills.
• Architect the capability constellation for jobs, skills, AI projections, and workforce capability.
• Integrate multi-source indicators of AI fluency personalized to job and AI foundation.
• Set the enterprise standard for workforce inference and validation.
• Lead design and implementation of the AI workforce strategy agent architecture.
• Design, train and maintain utility agents, super agents and orchestration layer.
• Enable talent strategy and partner with Future of Work and Capability Building stakeholders.
• Partner with Talent COE to integrate skills into talent systems and internal mobility.
• Own standards and governance for skills data across the talent ecosystem.

Skills

HR analytics

Talent COE

Workforce strategy

Data governance

Cross-functional

Executive communication

Program management

Stakeholder influence

Systems thinking

HR technology

Education

Bachelor's degree

Job description

Job Description Summary

GE Aerospace is developing a forward-looking AI workforce strategy ensuring the organization is prepared for how work, roles, and skills will evolve in the age of artificial intelligence. With a passion for amplifying what our people do best, unlocking new and higher-value work, and growing the human capabilities that will define the next era of aerospace, GE has created the AI workforce strategy function sitting at the intersection of the CHRO and the Chief Data & AI Officer.

Job Description

• Leads the establishing of AI workforce intelligence
• Establish the job and work AI inference foundation at the task level, connected to skills, and overlay the interaction of AI on those skills and tasks
• Establish the employee capability AI inference foundation, connecting employee profiles with skills, and overlaying the interaction of AI on those skills
• Architect the capability constellation to create a connected view of jobs, skills, AI projections, and workforce capability to inform effective employee capability growth and meaningful investments in employee development
• Integrate multi-source indicators of AI fluency hyper personalized to the job and work AI inference foundation
• Set the enterprise standard for workforce inference, establish the validation approaches, confidence thresholds for the enterprise
• Lead the design and implementation of the AI workforce strategy agent architecture
• Design, train and maintain the utility agents, super agents and orchestration layer spanning internal and external skills and job trends, talent supply, AI projection, AI workforce strategy, AI fluency and workforce-planning supplementation
• Enablement of talent strategy
• Partner with stakeholders representing Future of Work and Capability Building to optimize projections and the utility of the intelligence layer and agents
• Partner with Talent COE teams to integrate skills into talent systems, career architecture, and internal mobility programs
• Own the standards, governance model, and operating routines that keep skills data current, usable, and aligned across the talent ecosystem. The role partners closely with People Analytics, HR Technology, and Talent COE leaders to ensure skills are consistently defined, governed, and applied across key talent processes
• Preferred work location is Evendale, OH, however, remote employment will also be considered. Ability and willingness to travel at least 25%

Qualifications

• Bachelor's degree in human resources, organizational psychology, talent development, education, business, technology or a related discipline.
• 8-12+ years of experience in HR (e.g., people analytics, talent COEs, workforce strategy, HR technology), business intelligence/analytics, or related fields
• Experience designing data architecture and enabling intelligence infrastructure
• Experience with skills taxonomies, skills-based talent models, job architecture, data governance, or adjacent domains
• Proven ability to translate strategy into practical operating models, governance routines, and implementation plans
• Strong program and project management capability, including driving cross functional initiatives in complex, matrixed environments
• Experience working cross-functionally across HR, technology and business leadership to deliver enterprise solutions
• Strong ability to forge new territories where best practice and playbooks do not exist, and problem solve/solution
• Ability to develop credible influence as a collaborator with stakeholders
• Strong executive communicator with experience in moving from data to storytelling
• Strong systems thinker with the ability to connect underlying strategy, underlying technology and anticipate downstream needs or issues

Preferred

• Advanced degree in Human Resources, Organizational Development, Business, Industrial/Organizational Psychology, Strategy, or a related field
• Working knowledge of AI inference and talent intelligence
• Working knowledge of AI agents and how to apply agentic capabilities to data monitoring, interpretation, and synthesis
• Experience building or scaling organizational design, organizational effectiveness,