Lead Value Engineer - Energy

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

This role focuses on leveraging AI and automation solutions, specifically Celonis's Process Intelligence platform, to build data-driven business cases and drive adoption within the Energy sector. The Lead Value Engineer acts as a trusted advisor, architecting solutions that connect data across the value chain, focusing on operational and financial outcomes. Key responsibilities include identifying and framing value, building business cases, driving engagement success with AI-powered agents, orchestrating improvements with AI and automation, and providing product feedback 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. Build the Business Case: Construct robust, data-backed business cases by transforming operational and cost data into scored, visually ranked use cases with investment estimates and projected ROI.
  3. Drive Engagement Success: 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.
  4. Orchestrate Improvement: Guide customers on how to use AI and automation to streamline complex operational workflows, from field service management to grid modernization.
  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
  • Experience with API integration

Nice to have

  • granular knowledge of asset lifecycle management, upstream/downstream operations, grid modernization, and the broader energy value chain

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
  • LLM/prompt engineering
  • API integration

Other signals

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