Industry Consultant - AI for Energy

Introduction

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Your Role And Responsibilities

Core responsibilities

* Define and execute AI strategy for the Energy & Utilities vertical, aligned to global business objectives and market trends (generation, T&D, retail, DERs, storage, O&M).

* Translate industry pain points into prioritized AI use cases with clear business value (e.g., predictive asset maintenance, demand forecasting, DER orchestration, grid congestion management, energy trading optimization).

* Lead end-to-end solution definition from concept to production: requirements, data strategy, model selection, integration, and post-deployment monitoring and optimization.

* Own industry domain accuracy and relevance of AI solutions—ensure models and features reflect real-world physics, regulatory constraints and operational workflows.

Client engagement & go-to-market

* Lead client discovery and executive workshops to validate use cases, quantify ROI and build business cases for pilots and scale-ups.

* Support pre-sales by co-authoring proposals, solution architectures, demos and pricing with sales, product and technical teams.

* Act as the primary industry point-of-contact for strategic customers—manage expectations, secure stakeholder buy-in and drive adoption roadmaps.

Delivery & technical governance

* Collaborate with data engineers, ML engineers and cloud teams to ensure reliable data pipelines, reproducible models, secure cloud deployments and MLOps best practices.

* Define and enforce solution guardrails: data governance, model explainability, fairness, drift detection, versioning and rollback procedures.

* Ensure AI solutions integrate safely with OT and control systems; coordinate cyber/OT risk assessments and change-control processes.

Cross-functional leadership & capability building

* Build and maintain a library of reusable IP: reference architectures, templates, feature stores, trained models and playbooks for common energy use cases.

* Coach and upskill CoC members and customer teams on energy domain knowledge, AI literacy, and adoption practices (trainings, brown-bags, proof-of-value clinics).

* Recruit and grow a multi-disciplinary team (industry SMEs, data scientists, ML engineers, product managers) and align staffing to demand.

Partnerships & ecosystem

* Develop and manage partnerships with hyperscalers, analytics vendors, grid software providers, hardware OEMs and academic research groups to accelerate delivery.

* Keep an active network in industry consortia, standards bodies and regulator forums to track regulatory changes and influence standards relevant to AI in energy.

Preferred Education

Doctorate Degree

Required Technical And Professional Expertise

* Deep energy & utilities domain knowledge (generation, transmission, distribution, retail markets, DERs, O&M)

* Practical AI/ML understanding: model lifecycle, MLOps, data engineering and cloud-native deployment patterns

* Experience integrating AI into OT systems and knowledge of OT/IT convergence risks

* Strong client-facing and stakeholder management skills; able to translate technical capability into business outcomes

* Cross-functional leadership, delivery management and proven track record of taking pilots to production