About the role
- Strategic AI Enablement:
- Define and execute the roadmap for our internal AI projects, including data architecture, model selection, and secure deployment pipelines.
- Ensure PCS project delivery guidelines are compliant to GE Vernova process while working to enable fast, nimble project delivery.
- Work Stream Leadership: Provide direct leadership and oversight to five dedicated AI Work Stream Leads. You will set the cadence for progress, ensure cross-pollination of best practices, and hold them accountable for tangible productivity improvements in their respective functions.
- Cross-Functional Transformation:
- Engineering: Accelerate NPI programs & software development, reduce ITO delivery cycle times while leveraging product platforming, and streamline project engineering processes with AI Agents.
- Services: Improve asset uptime and predictive maintenance accuracy. Improve data access and product information availability to services engineering team.
- Manufacturing: Optimize throughput and quality control through computer vision, process analytics and other automated methods.
- Sourcing: Leverage predictive analytics to optimize supply chain resilience and cost.
- Commercial: Enhance lead conversion and customer pricing models.
- Change Management: Act as a champion for an AI-first culture, driving adoption, addressing technical debt, and ensuring our workforce is upskilled to collaborate with AI tools.
- Governance & Compliance: Establish robust guardrails for AI ethics, data privacy, and intellectual property protection in line with GE Vernova standards.
- Productivity: Work to implement best practicing sharing, remove duplication of work, and ensure organization follows a robust tool validation process.
Qualifications
- Experience: 12+ years in technical leadership roles, with at least 5 years specifically focused on leading enterprise-scale AI/ML transformations.
- Industry Knowledge: Deep understanding of Power Conversion, Energy Storage, or related industrial sectors is highly preferred.
- Leadership: Demonstrated experience managing cross-functional teams and influencing senior stakeholders. Ability to translate technical AI jargon into clear business value.
- Technical Acumen: Hands-on experience with modern AI stacks (LLMs, predictive modeling, data engineering). Ability to guide architectural decisions regarding "build vs. buy."
- Education: Master’s degree or PhD in Computer Science, Data Science, Engineering, or a related field; MBA is a plus.
Relocation Assistance Provided: Yes