SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Celonis is seeking a Senior Value Engineer to drive customer success and value realization for enterprise clients using its Process Intelligence platform. In this role, you will serve as a trusted advisor to strategic customers, guiding them through their entire value journey from pre-sales discovery through post-implementation adoption and expansion.
You will own the end-to-end customer lifecycle, blending process expertise with a solution-first mindset. Key responsibilities include leading technical discovery and capability demonstrations during pre-sales cycles, managing implementation to ensure agreed value thresholds are met, and driving enterprise-wide ROI and adoption programs. You will establish repeatable frameworks for customers to independently track and expand business value, conduct quarterly business reviews with VP+ level executives, and manage multiple customer projects at different stages simultaneously.
As a domain expert, you will serve as the internal and external technical subject matter expert for your customer industry vertical, scaling knowledge across the organization. You will understand customers' AI strategies and challenges, translating requirements into innovative solutions using Celonis's Process Intelligence Graph and AI/LLM capabilities to help customers move from simple automation to intelligent, autonomous agents that solve complex business bottlenecks.
Required qualifications include 4+ years in pre-sales, customer success, consulting, strategy consulting, business process improvement, or digital transformation. You must have strong technical skills across Microsoft Azure or equivalent platforms (AWS), with certifications in relevant technologies and knowledge of data connections, data engineering, and LLM tools (Copilot, Claude, etc.). You should demonstrate expertise in value-driven selling, project management across multiple accounts, and strong presentation skills for both technical and executive audiences. A bachelor's degree in computer science, engineering, mathematics, or related field is required, or equivalent work experience.
Nice-to-have qualifications include understanding of business processes in supply chain or finance, Python proficiency with ML libraries (LangChain, pandas, sklearn, PyTorch), and hands-on experience building agentic systems using LLM orchestration, RAG, and prompt engineering.
