Senior Value Engineer

Celonis Celonis · Data AI · New York, NY +2 · Value Engineering

This role is a Senior Value Engineer at Celonis, an enterprise SaaS company specializing in Process Intelligence. The role involves working with strategic clients to understand their objectives, analyze customer data, and deploy solutions using the Celonis platform. A key aspect is leveraging the platform to feed operational context to AI and LLM tools, enabling customers to deploy intelligent, autonomous agents. The role requires pre- and post-sales execution, AI discovery and solutioning, and demonstrating value to executives. While the company uses AI extensively and the role involves understanding and applying AI/LLM solutions for customers, the primary focus is on customer value realization and solution deployment rather than core AI/ML model development.

What you'd actually do

  1. Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales expansion cycles and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully met.
  2. Owns driving enterprise-wide ROI and adoption programs. Increasingly accelerates customer autonomy with improved cadences and executive sponsorship through QBRs, strategic roadmaps, and enterprise-wide value opportunities. Enables cross-functional alignment and establishes repeatable frameworks for customers to independently track, realize, and expand on business value.
  3. Understand your customers' AI strategies and specific challenges. As a Celonis product expert, find the best problem-solution fit and translate customer requirements into innovative solutions that deliver measurable impact.

Skills

Required

  • 4+ years of experience in pre-sales, customer success, and/or consulting functions
  • Strong Technical Skills across Microsoft or competitor equivalent (e.g., AWS) certification in relevant technologies (e.g. Azure, Data Engineering..etc).
  • Knowledge of Data Connections, Data Objects, Data Validation and Data Analysis.
  • Knowledge and use of LLM’s, across Microsoft or competitor equivalent (e.g. Claude, Copilot…etc).
  • Understanding of basic prompting and data constructs within a prompt.
  • Value driven selling through expertise in identifying and prioritising use cases, implementing improvement measures and becoming a change agent for the customer by establishing an operating model and training users for the customer to realize value and renew/expand their subscription with Celonis
  • Project Management: You are able to plan and manage project scope, expectations and timelines.
  • Strong presentation skills to both internal and external stakeholders, whether leading technical whiteboarding sessions or formal readouts and demos.
  • Bachelor’s Degree required; Focus in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred.

Nice to have

  • Understanding of business processes across sectors (such as Supply Chain or Finance) with the ability to translate high-level business needs into specific AI use cases.
  • Good knowledge of Python and common ML libraries (such as LangChain, pandas, sklearn, PyTorch) as well as data engineering tools and technologies.
  • Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.

What the JD emphasized

  • 4+ years of experience in pre-sales, customer success, and/or consulting functions
  • Knowledge and use of LLM’s
  • Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, while ensuring safety through rigorous evaluations and guardrails.

Other signals

  • enterprise SaaS
  • Process Intelligence Graph
  • advanced AI capabilities
  • deploying an agentic business
  • deploy intelligent, autonomous agents
  • customers' AI strategies
  • translate customer requirements into innovative solutions
  • use of LLM’s
  • building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering