Job Description Summary

As a Sr Technical Project Manager – Finance AI & Automation, you will help shape and execute the Finance AI strategy for HQ Finance DT, driving measurable value through automation, data, and AI-enabled solutions. In partnership with Digital Technology, Finance leaders, and functional subject matter experts across HQ and segment business units, you will define priorities, establish a disciplined intake and governance process, and ensure solutions are aligned to business needs, scalable, and sustainable.
This role is responsible for leading AI initiatives across Finance DT value streams by working with DT leaders, finance process owners, and technology teams across HQ and the business units. You will identify and prioritize use cases, translate business requirements into functional specifications, support conceptual design, and drive delivery across enterprise and custom applications. Close collaboration with the BU teams, GE Vernova Data & Analytics, and the AI Foundry is essential to executing the strategy and delivering business outcomes.

Job Description

Roles & Responsibilities:

• Champion a culture of rapid experimentation by establishing lightweight, iterative frameworks that enable Finance DT teams to quickly prototype, test, and validate AI-based solutions.

• Support AI adoption and upskilling initiatives, including education programs, hands-on workshops, and awareness campaigns, to continuously elevate AI IQ across Finance DT and Finance stakeholder groups — fostering a proactive, innovation-driven mindset aligned to GE Vernova's broader AI strategy.

• Partner with HQ and segment leadership to define and execute the Finance AI strategy and roadmap.

• Lead Finance AI initiatives across Finance DT, ensuring alignment with functional teams, the GE Vernova AI Foundry, and HQ Data & Analytics.

• Develop and maintain a multi-year roadmap of high-value AI use cases across Finance, including centralized reporting in partnership with the AI Foundry.

• Collaborate with the AI Foundry and Finance software engineering teams to integrate AI capabilities into enterprise and custom-built applications.

• Lead AI-enabled initiatives across a portfolio of 40+ applications, including ML, GenAI, and Agentic AI solutions.

• Establish a structured intake, evaluation, and prioritization process to identify the right opportunities and avoid unnecessary technical debt.

• Promote strong data governance and operational discipline across Finance automation technologies.

• Lead AI awareness, education, and upskilling efforts for Finance DT and Finance stakeholders.

• Serve as a trusted advisor and communication bridge to Finance and DT leadership, providing clear updates on progress, risks, benefits, and business impact.

• Define and track KPIs and success measures to demonstrate value, efficiency gains, and measurable outcomes from AI deployments.

• Contribute to the continuous improvement of delivery practices, governance models, and toolsets for AI and multi-generation product development in an enterprise environment.

 

Qualifications:

Mandatory Qualifications

• Bachelor’s degree in Business, Computer Science, or a STEM discipline.

• GE Vernova leadership pipeline graduate or a work experience of 3+ years in stakeholder engagement, product management, and project management.

 

 

Desired Characteristics

• Strong understanding of business priorities, operating models, and cross-functional processes.

• Ability to connect individual deliverables to broader organizational and business outcomes.

• Proven track record of driving collaboration across business and digital teams.

• Comfortable operating in ambiguous environments and making sound decisions within defined guardrails.

• Strong analytical and problem-solving skills, with the ability to use data and insights to drive action.

• Skilled at navigating complex organizations and aligning diverse stakeholders around a common goal.

• Able to anticipate risks and barriers, develop effective workarounds, and use available resources efficiently.

• Strong awareness of the technology landscape to support make-buy-build decisions and MVP scoping.

• Ability to articulate business value clearly, assess alternative approaches, and apply Lean principles in a dynamic environment.

Additional Information