Senior Value Engineer - Energy Industry

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

Senior Value Engineer for the Energy Sector, focusing on applying Celonis' Process Intelligence platform with AI/ML partners to solve business-critical problems for energy clients. Responsibilities include understanding customer AI strategies, prototyping solutions using generative AI techniques (RAG, agents, multimodal), leading pre- and post-sales engagements, and executing Proof-of-Value projects involving LLM/agent systems with RAG, tools, and guardrails, while adhering to energy compliance frameworks.

What you'd actually do

  1. Understand energy customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, or regulatory compliance). As a Celonis product and energy domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle.
  2. Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached.
  3. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to power generation, transmission, and O&G operations.
  4. Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement).
  5. End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks.

Skills

Required

  • Python
  • LangChain
  • pandas
  • pydantic
  • sklearn
  • PyTorch
  • RAG
  • prompt engineering
  • multi-agent orchestration
  • multimodal understanding
  • fine-tuning
  • LLM orchestration
  • function calling
  • evaluations
  • guardrails
  • enterprise data integration
  • identity protocols
  • energy compliance frameworks

Nice to have

  • LangChain
  • LlamaIndex
  • AWS Bedrock
  • Azure AI
  • GCP Vertex
  • IT/OT convergence
  • industrial IoT data structures

What the JD emphasized

  • 5+ years of experience leading technical pre-sales and post-sales engagements specifically within the Energy sector
  • Deep understanding of business processes native to the Energy sector
  • Expertise in generative AI techniques like RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, or fine-tuning used to build high-impact use cases
  • Solid knowledge of Python and common ML libraries
  • stringent energy compliance frameworks

Other signals

  • industrialize AI
  • deployments at scale
  • secure, scalable LLM/agent systems
  • autonomous AI agents