Job Description Summary

The AI & Analytics Delivery PMO is responsible for leading end-to-end delivery governance, portfolio execution, integrated planning, and operational management across Analytics and AI initiatives within Power. This leadership role establishes the operating mechanisms required to manage a complex portfolio of Big Swing and non-Big Swing AI initiatives, while ensuring strong alignment across AI Strategy, Power AI Delivery, business AI program leaders, Data & Analytics teams, and strategic delivery partners.

Serving as the central orchestration point for Data, Analytics, and AI delivery across Power, this leader will establish delivery governance, operating rhythms, portfolio visibility, Program Increment (PI) planning, capacity and dependency management, and consistent execution standards. The role will translate prioritized demand and strategic roadmaps into executable delivery plans, ensuring the appropriate capacity, capabilities, sequencing, and governance are in place to deliver committed outcomes with quality and predictability.

As the Release Train Engineer (RTE) for initiatives owned by the Power AI Delivery team, this individual will lead overall PI governance in partnership with Scrum Masters, facilitate cross-team planning and synchronization, proactively manage risks and dependencies, remove systemic impediments, and drive continuous improvement across the delivery organization. The role will partner closely with business AI program managers and delivery teams to establish clear accountability, strengthen execution discipline, and ensure predictable, on-time delivery from Proof of Concept through production deployment and adoption.

Beyond AI delivery, the AI & Analytics Delivery PMO will provide integrated governance across Business Intelligence and Data delivery, ensuring that foundational data, analytics, and reporting initiatives remain aligned with AI priorities and the broader Power Data & Analytics roadmap.

Job Description

Roles and Responsibilities

In this role, you will:

• Data, Analytics & AI Portfolio Delivery Governance: Establish and lead the overall delivery governance framework for Data, Analytics, and AI initiatives across Power, including both Big Swing and non-Big Swing AI programs. Partner with the AI Foundry, AI Strategy Portfolio team to translate portfolio priorities into disciplined execution while maintaining clear ownership between strategy, business sponsorship, and delivery.
• Program Increment & Integrated Capacity Planning: Own and facilitate the Program Increment planning process for Power AI-delivered programs. Translate prioritized demand and product roadmaps into integrated capacity plans across internal teams and strategic partners, balancing business priorities, available skills, delivery constraints, and committed timelines.
• Release Train Engineer Leadership: Serve as the Release Train Engineer Lead for AI initiatives delivered by the Power AI Delivery team. Lead PI Planning, ART synchronization, program-level execution rhythms, dependency resolution, risk management, retrospectives, and continuous-improvement activities to improve delivery predictability and organizational velocity.
• End-to-End Delivery Management: Partner with business AI program managers, technical delivery leaders, and strategic partners to ensure initiatives progress effectively through the full delivery lifecycle—from data readiness and Proof of Concept through MVP, production deployment, and operational transition—with appropriate quality, governance, and accountability at each stage.
• Delivery Performance & Quality Management: Establish clear delivery milestones, quality gates, KPIs, and portfolio health measures. Monitor schedule, scope, capacity, risks, dependencies, and delivery quality, proactively identifying execution gaps and driving corrective actions before they impact business commitments.
• Cross-Program Dependency & Risk Management: Maintain an integrated view of dependencies across AI, Data, BI, architecture, platforms, cybersecurity, infrastructure, ERP, and other enabling teams. Proactively identify systemic impediments, facilitate resolution across organizational boundaries, and escalate critical risks where leadership intervention is required.
• Business & Cross-Functional Partnership: Build strong partnerships with business AI program managers, AI Strategy, Data & Analytics teams, Digital Technology, OCIO, functional leaders, and strategic delivery partners to align priorities, roles, expectations, and execution plans.
• Data & Analytics Delivery Governance: Provide portfolio-level governance and execution oversight for Business Intelligence, Data, and Analytics delivery across Power, ensuring that foundational data and analytical capabilities are delivered with appropriate quality, scalability, and alignment to business and AI priorities.
• Integrated AI, Data & BI Roadmap Alignment: Ensure AI initiatives are appropriately connected to underlying Data and BI roadmaps. Identify common capabilities, shared data dependencies, reusable data products, and opportunities to reduce duplicated investments while improving scalability across the Power portfolio.
• AI Production Readiness & Operational Transition: Define and enforce production-readiness requirements for AI solutions, ensuring clear ownership, operational support models, monitoring, documentation, service expectations, and transition criteria are established prior to production deployment.
• Portfolio Operating Rhythm & Executive Visibility: Establish consistent portfolio operating rhythms and executive-level reporting that provide transparent visibility into delivery health, capacity, milestones, risks, dependencies, quality, resource constraints, and required decisions. Manage Big swing AI Delivery Bowler for regular leadership update
• Demand-to-Delivery Alignment: Partner with the AI Strategy Portfolio team and business stakeholders to ensure approved demand is appropriately sequenced, delivery-ready, and aligned with available capacity before entering execution. Provide feedback into portfolio prioritization based on delivery complexity, dependencies, technical readiness, and resource requirements.
• Standard Work & Delivery Excellence: Define and continuously improve standard work across demand transition, PI planning, execution governance, status reporting, quality management, production readiness, and operational support. Drive consistency while maintaining flexibility for different initiative sizes and delivery models.
• Continuous Improvement & Productivity: Apply Agile, SAFe, Lean, automation, and structured problem-solving practices to reduce delivery friction, improve cycle time and productivity, strengthen delivery predictability, and continuously mature the Power Data, Analytics, and AI delivery operating model.

Qualification

• Bachelor’s degree in business, Computer Science, Information Systems, Engineering, Data Analytics, or a STEM-related field, including Science, Technology, Engineering, or Mathematics.
• Minimum of ten years of experience in technology program management, Data & Analytics delivery, Artificial Intelligence, Business Intelligence, digital transformation, or a related discipline.
• Minimum of eight years of experience leading complex cross-functional programs, portfolios, or technology delivery initiatives involving multiple business, technical, and partner organizations.
• Demonstrated experience leading Agile and/or SAFe delivery processes, including Program Increment planning, capacity planning, dependency management, release planning, risk management, and portfolio-level execution governance.
• Demonstrated experience managing enterprise Data, Analytics, BI, AI, or digital programs through multiple stages of the delivery lifecycle, from planning and development through production implementation and operational transition.
• Proven ability to lead complex initiatives across organizational boundaries, influence without direct authority, and establish accountability among business, technology, and external partner teams.
• Demonstrated success improving delivery predictability, governance, execution discipline, or operating models across large-scale transformation programs.

Desired Characteristics

• AI & Analytics Delivery Expertise: Strong understanding of the end-to-end Data, Analytics, and AI delivery lifecycle, including data readiness, architecture, Proof-of-Concept execution, MVP development, integration, production deployment, operationalization, and ongoing lifecycle management.
• Portfolio & Program Leadership: Demonstrated ability to manage a portfolio of concurrent initiatives with competing priorities, constrained resources, cross-program dependencies, and varying levels of technical and business complexity.
• Agile & SAFe Leadership: Strong experience with Agile and SAFe methodologies, particularly Program Increment planning, Agile Release Trains, capacity planning, program synchronization, dependency management, Inspect & Adapt, and continuous improvement. Prior experience as a Release Train Engineer, Agile Program Lead, or equivalent role is highly desirable.
• Delivery Governance & Execution Discipline: Proven ability to establish delivery frameworks, quality gates, governance mechanisms, KPIs, risk-management processes, and executive operating rhythms that increase transparency, accountability, and predictability.
• Technical Proficiency: Working knowledge of enterprise Data and Analytics technologies such as Power BI, Tableau, SQL, SAP, Oracle, and Databricks. Familiarity with cloud, big data, AI/ML, Generative AI, MLOps/AI Ops, APIs, integration technologies, and modern enterprise data architectures is highly desirable.
• Strategic Planning & Capacity Management: Strong ability to translate strategic priorities and portfolio demand into practical roadmaps, delivery plans, resource models, capacity requirements, sequencing decisions, and executable commitments.
• Cross-Functional Leadership: Demonstrated ability to orchestrate execution across Business, AI Strategy, Data Science, Architecture, Digital Technology, Data & Analytics, ERP, cybersecurity, infrastructure, and external partners while driving accountability without relying on direct organizational authority.
• Executive Stakeholder Management: Ability to synthesize complex delivery, technical, financial, and resource information into clear executive-level insights and recommendations. Comfortable facilitating prioritization, trade-off, and escalation discussions with senior business and technology leaders.
• Governance & Risk Management: Strong understanding of enterprise technology governance, including architecture, cybersecurity, data governance, privacy, internal controls, regulatory requirements, and production-readiness standards.
• Process Improvement: Experience applying Lean principles, structured problem-solving, Agile retrospectives, automation, and continuous-improvement methodologies to simplify processes, establish scalable standard work, eliminate delivery bottlenecks, and improve organizational productivity.
• Influential Communication: Exceptional interpersonal, facilitation, and communication skills, with demonstrated ability to create clarity in ambiguous environments, align diverse stakeholder groups, resolve competing priorities, and maintain momentum across complex transformation programs.
• Ownership & Results Orientation: Strong sense of accountability with the ability to proactively identify risks and opportunities, drive decisions, remove barriers, and consistently deliver against commitments in a fast-paced and evolving Data and AI environment.

 

 

For candidates applying to a U.S. based position, the pay range for this position is between $155,300.00 and $258,800.00. The Company pays a geographic differential of 110%, 120% or 130% of salary in certain areas. The specific pay offered may be influenced by a variety of factors, including the candidate’s experience, education, and skill set.

 

 

Bonus eligibility: discretionary annual bonus.

 

 

This posting is expected to remain open for at least seven days after it was posted on August 18, 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 resources and financial planning consultants. Other benefits include tuition assistance, adoption assistance, paid parental leave, disability benefits, life insurance, 12 paid holidays, and permissive time off.

 

 

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.