Senior Consultant, AI & Automation (Energy, Mining & Utilities)

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: Our team is seeking an experienced consultant who understands how energy, mining, and utilities companies operate and who is passionate about applying AI and intelligent automation to their toughest operational challenges. As a Senior Consultant, AI & Automation Delivery (Energy, Mining & Utilities), you will help oversee the execution of intelligent automation and AI projects across asset-heavy industries. You will bridge complex industrial operations and technical execution, providing delivery oversight and supporting Solution Architects as they modernize legacy workflows. You will deliver your own work while coordinating a small team of consultants to an outcome, working alongside Managing Consultants and holding relationships with senior and manager-level client stakeholders. Key responsibilities include: Project & Delivery Oversight: Lead the delivery of workstreams on AI, machine learning, and intelligent automation projects across power generation, grid operations, drilling, processing plants, and corporate functions. Coordinate 2 to 5 consultants to a deliverable, or act as project manager alongside a Managing Consultant, tracking scope, timeline, and effort throughout. Architect Enablement: Support Solution Architects by translating complex operational realities (e.g., operational technology constraints, safety-critical workflows) into detailed functional specifications, and confirm that technical designs align with business value. Stakeholder Management: Act as a core liaison between plant and field operations managers, senior client stakeholders, and technical delivery teams, turning industrial challenges into structured AI delivery streams. Lead client working sessions and manage expectations directly, including difficult conversations. Operational Risk & Governance: Proactively manage project risks, including data silos, legacy infrastructure integration, safety compliance, and change management for field workforces. Flag scope creep and commercial risk to engagement leadership early. AI-Assisted Delivery: Build reusable AI-assisted workflows for the team’s deliverables (research, analysis, drafting, quality assurance), own the quality of AI-assisted output, and coach junior consultants to use these workflows well. Business Development: Contribute materially to RFPs and proposals, including solution narrative, approach, and effort estimates, and identify extension opportunities within current engagements. Practice Growth: Contribute to the practice’s digital transformation frameworks and reusable assets, support recruiting, and mentor junior consultants in energy-sector technology delivery. You will provide conceptual oversight and work with solution architects, developers, and data scientists on projects such as: Predictive Maintenance & Asset Management: AI models that predict equipment failures in mines, mills, pipelines, or grid infrastructure. Operational Automation: Automating supply chain, workforce dispatch scheduling, or field inspection data ingestion (e.g., drone and IoT data workflows). Sustainability & ESG Tracking: Automated carbon emissions tracking, environmental monitoring, or energy grid optimization. Generative & Agentic AI for Operations: Knowledge assistants and agentic workflows for maintenance procedures, engineering documentation, and regulatory reporting. You’ll be part of a collaborative environment where diverse perspectives are valued, and where team members are encouraged to take initiative, think critically, and contribute to meaningful outcomes for clients. This opportunity is for a hybrid position, based out of Calgary or Toronto. Bachelor’s or Master’s degree in, Business, Engineering, Computer Science, or a related field 4+ years of professional technology consulting or project delivery experience Minimum 2 years working directly within or consulting for the Energy, Oil & Gas, Mining, or Utilities sectors, with a working understanding of core industrial paradigms (e.g., upstream and downstream, grid distribution, fixed-plant operations, IT and OT environments) Strong working knowledge of Agile, Scrum, or Stage-Gate delivery frameworks, with experience managing delivery velocity, scope creep, and cross-functional dependencies Demonstrated experience coordinating small teams to a deliverable, including delegating work, reviewing output, and giving specific, actionable feedback Ability to frame ambiguous problems, define hypotheses, and land recommendations that hold up under senior and client challenge Strong communication skills, including leading client workshops (e.g., design thinking), writing client-ready deliverables, and translating technical findings for non-technical audiences Ability to navigate traditional, asset-heavy corporate structures and to confidently challenge and collaborate with senior technical architects Working fluency in the AI landscape, including foundation models, agent frameworks, and automation platforms, with the ability to explain build, buy, and fine-tune trade-offs Hands-on fluency with AI tools and agentic workflows, and sound judgment in using AI responsibly, including verifying outputs and protecting sensitive information Fluent in English Project or delivery certification such as PMP or Certified ScrumMaster (CSM) Practitioner-level AI credential (e.g., Azure AI Engineer Associate (AI-102), AWS Certified Machine Learning Engineer Associate, Google Professional Machine Learning Engineer) or foundational cloud credentials such as AWS Cloud Practitioner or Azure Fundamentals Canada Consulting Hybrid Professional Multiple Cities (0026) IBM Canada Limited - IBM Canada Limitee