Lead Value Engineer - Energy

Celonis Celonis · Data AI · New York, NY · Value Engineering

This role focuses on leveraging AI and automation solutions within the energy sector to drive business value and operational improvements. The Lead Value Engineer will act as an architect for SaaS adoption, building data-driven business cases, identifying high-impact areas, and leading the implementation of AI-powered solutions. The role involves translating strategy to operations, architecting solutions connecting data across the value chain, constructing business cases, and driving customer engagements to realize measurable business impact. Key responsibilities include designing and deploying AI-powered feedback agents, guiding customers on AI/automation for operational workflows, and providing feedback to product teams based on AI agent development and LLM/prompt engineering experience.

What you'd actually do

  1. Translate Strategy to Operations: Analyze the client’s strategic priorities and map end-to-end energy operations (e.g., exploration and production, refining, or grid distribution) to AI-driven improvement use cases.
  2. Architect solutions that connect data across the value chain, focusing on critical energy operations like predictive maintenance workflows, supply chain optimization, outage reporting automation, and asset performance dashboards.
  3. Construct robust, data-backed business cases by transforming operational and cost data into scored, visually ranked use cases with investment estimates and projected ROI.
  4. Lead the value workstream by designing and deploying AI-powered feedback agents capable of ingesting 10,000+ operational data points to surface recurring themes and friction points in the field or at the plant.
  5. Provide feedback to our product development teams based on hands-on AI agent development, LLM/prompt engineering, and API integration experience.

Skills

Required

  • 10 years of experience in the Energy sector (Oil & Gas, Power generation, or Utilities)
  • Management Consulting (Strategy & Operations Transformation) experience
  • Deep process expertise
  • Strong analytical skills
  • AI-solution mindset
  • Experience with AI agent development
  • Experience with LLM/prompt engineering
  • API integration experience
  • Experience with enterprise health check assessments
  • Experience facilitating workshops with C-suite and field department leads
  • Experience building data-driven business cases
  • Experience with predictive maintenance workflows
  • Experience with supply chain optimization
  • Experience with outage reporting automation
  • Experience with asset performance dashboards
  • Experience with HSE (Health, Safety, and Environmental) and regulatory compliance requirements
  • Experience with success metrics and KPIs
  • Experience with pilots
  • Experience with performance dashboards to track financial and operational KPIs

Nice to have

  • Experience with Process Intelligence platform
  • Experience with Process Mining technology
  • Experience with cloud software adoption
  • Experience with 3-year strategic transformation roadmaps

What the JD emphasized

  • 10 years of experience in the Energy sector
  • Management Consulting (Strategy & Operations Transformation) is required
  • AI-driven improvement use cases
  • AI and automation solutions
  • AI-powered feedback agents
  • AI agent development
  • LLM/prompt engineering

Other signals

  • AI-driven improvement use cases
  • AI and automation solutions
  • AI-powered feedback agents
  • AI agent development
  • LLM/prompt engineering