Job Description Summary

The Director of AI Strategy & Transformation for Wind Engineering will establish and lead the application of Artificial Intelligence (AI) as a scalable and value-generating capability across the Wind Engineering organization. This role is accountable for defining the AI vision and roadmap building the organizational and technical systems required to scale and ensuring AI initiatives deliver measurable business outcomes.

As a newly created leadership role this position requires a leader who can operate effectively in uncertainty shape strategy while driving execution and build durable structuresincluding governance operating models and partnershipsthat enable sustained impact.

Job Description

Key Responsibilities:

AI Strategy Vision & Value Delivery

• Define and own the AI strategy and multi-year roadmap for Wind Engineering aligned with business priorities and enterprise AI direction.
• Identify prioritize and sequence high-value AI use cases across design analysis validation manufacturing support operations reliability and lifecycle optimization.
• Establish clear value hypotheses success metrics and ROI tracking for AI initiatives.
• Ensure balance between rapid experimentation and development of scalable repeatable capabilities.

Scalable Systems Platforms & Governance

• Design and implement AI systems that scale including standards for data models tooling deployment and lifecycle management.
• Establish and lead AI governance for Wind Engineering including:
  • Model risk management and validation
  • Data quality lineage and access standards
  • Responsible AI safety and regulatory compliance
  • Decision rights and investment prioritization
• Partner with Digital IT and Data leaders to align on platform strategy architecture and MLOps practices.
• Ensure AI solutions are maintainable auditable and reusable across products and teams.

Organizational Design & Talent Leadership

• Define the AI operating model for Wind Engineering (centralized federated or hybrid) including roles interfaces and engagement models.
• Build lead and develop a high-performing team of AI engineers data scientists and technical leaders within this operating model.
• Define capability requirements skill profiles and career paths for AI-enabled engineering roles.
• Lead hiring onboarding and succession planning for critical AI leadership and technical roles that would include direct and indirect reporting lines.

Adoption Change & Engineering Integration

• Drive broad adoption of AI within engineering embedding AI tools workflows and decision-support into standard engineering processes.
• Lead identification of core AI skillsets required across the entire Wind Engineering team. Incorporate these into competency models and work to develop and institute training as required.
• Partner with engineering leaders to integrate AI into design reviews validation workflows and operational decision-making.
• Lead change management efforts including training communications and communities of practice to increase AI fluency and trust.
• Establish feedback loops to continuously improve usability effectiveness and adoption.

External Partnerships & Ecosystem Development

• Develop and manage strategic external partnerships with AI technology providers software vendors startups universities and research institutions.
• Evaluate when to build buy or partner to accelerate capability development and value realization.
• Structure and govern partnerships to ensure IP protection scalability security and long-term value.
• Represent Wind Engineering in external forums and collaborations related to AI and advanced engineering methods.

Cross-Business Collaboration

• Serve as a partner to Product Management Supply Chain Services Commercial and Enterprise Digital teams to ensure AI initiatives deliver end-to-end business impact.
• Align Wind Engineering AI efforts with enterprise AI standards platforms and investments influencing direction where needed.
• Enable reuse and scaling of AI solutions across functions regions and product lines.

Leadership in Ambiguity

• Translate ill-defined problems and emerging opportunities into clear strategies executable plans and scalable solutions.
• Make informed tradeoffs across speed risk technical depth and business value.
• Set direction and maintain momentum in a rapidly evolving technology and business landscape.

Qualifications & Experience

Required

• Bachelors degree in Engineering Computer Science Applied Mathematics or related field (advanced degree strongly preferred).

Preferred

• Extensive experience in engineering leadership digital transformation or advanced analytics/AI within a complex industrial environment.
• Proven ability to design and lead governance operating models and scalable systems.
• Experience building and leading multidisciplinary teams.
• Strong executive communication and stakeholder management skills.
• Demonstrated success delivering AI-enabled business outcomes at scale not just pilots or proofs of concept.
• Experience in wind energy power generation aerospace or similarly regulated safety-critical industries.
• Experience managing external partnerships and joint development initiatives.
• Familiarity with enterprise data platforms cloud-native AI solutions and MLOps frameworks.
• Experience operating in matrixed global organizations.

Critical Success Factors

• Ability to create structure and momentum in ambiguity.
• Credibility with senior engineering digital and business leaders.
• Strong systems thinkingconnecting data models people and processes into scalable capability.
• Results orientation with a disciplined approach to governance and risk.

Why This Role Matters

This Director role will define how AI becomes a core trusted and scalable capability within Wind Engineering enabling faster innovation improved product performance reduced risk and differentiated customer value. The decisions made in this role will shape engineering practices for years to come.

For candidates applying to a U.S. based position the pay range for this position is between $220000 and $300000. The specific pay offered may be influenced by a variety of factors including the candidates experience education and skill set.

For candidates applying to a U.S. based position only:

Bonus eligibility: discretionary annual bonus.

This posting is expected to remain open for at least seven days after it was posted on April 20 2026.

Available benefits include medical dental vision and prescription drug coverage; access to Health Coach from GE Vernova a 24/7 nurse-based resource; and access to the Employee Assistance Program providing 24/7 confidential assessment counseling and referral services. Retirement benefits include the GE Vernova Retirement Savings Plan a tax-advantaged 401(k) savings opportunity with company matching contributions and company retirement contributions as well as access to Fidelity Executive Services. Other benefits include tuition assistance adoption assistance paid parental leave disability benefits life insurance 12 paid holidays and permissive time off and the Restoration Plan a nonqualified plan with company credits on eligible pay above IRS limits.

GE Vernova Inc. or its affiliates (collectively or individually GE Vernova) sponsor certain employee benefit plans or programs GE Vernova reserves the right to terminate amend suspend replace or modify its benefit plans and programs at any time and for any reason in its sole discretion. No individual has a vested right to any benefit under a GE Vernova welfare benefit plan or program. This document does not create a contract of employment with any individual.