The Role:

As a Value Engineer, you are spearheading our mission of solving critical operational challenges for enterprise customers. You will be working with strategic clients to understand their unique objectives, from modernizing legacy systems to optimizing finance processes and deploying an agentic business. In partnership with the Celonis Sales Teams, you have full responsibility for the end-to-end value journey of our customers. You are our customers' trusted advisor and help them drive adoption and realize measurable business value using Celonis.

You can expect to blend process and industry expertise with a solution-first mindset, analyzing customer data and deploying tactical solutions. By using the Celonis Process Intelligence platform to feed critical operational context to AI and LLM tools, you will help our customers move past simple automation to deploy intelligent, autonomous agents that solve complex business bottlenecks. You’re the Celonis expert, connecting the dots between their pain points and how our platform can solve the problem. You’d be managing weekly cadences, QBRs, and value plans to demonstrate the value of our solutions to VP+ level executives.

Key Responsibilities:

• Pre- and Post-Sales Execution: 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.

Insights framing and value realization: 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.Domain & Industry Leadership:  Serve as the internal and external technical subject matter expert for your customer industry domain to scale knowledge across the organization.

• AI Discovery & Solutioning: 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.

Requirements:

• 7+ years of experience in pre-sales, customer success, and/or consulting functions with a background in pre/post- sales consulting, strategy consulting, business process improvement, digital transformations, or customer value realization
• 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. You will need to manage multiple projects across your aligned accounts that will be at different parts of the value journey. Also, you will leverage partners from the Celonis Ecosystem wherever possible.
• 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 (big plus):

• 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.