The opportunity
Celonis is the trusted platform to industrialize Enterprise AI. At our core is the Celonis Context Model — which combines process data, business knowledge, and intelligence into a living digital twin of the enterprise that AI can actually understand, turning AI's operational blind spots into operational clarity.
What you'll do
Discovery & Solution Blueprinting: Conduct collaborative discovery workshops to uncover root-causes and operational inefficiencies, mapping ambiguous customer needs into clear technical scopes and comprehensive solution blueprints.
Context Model & Solution Deployment: Execute hands-on deployments of customer-specific context models, data structures, and end-to-end supply chain blueprints within the Celonis platform.
Project Management & Customer Value: Own customer deployments end-to-end from initial kickoff to live production, presenting complex architectural solutions and strategic value narratives directly to cross-functional stakeholders and executive teams.
Prototype & Test Functions: Design, validate, and test use-case-specific decision intelligence functions, including e.g. optimization algorithms and predictive models.
Context Generation: Deconstruct monolithic application architectures and translate deployment learnings into reusable semantic entities and modular context libraries.
+ years of experience as a Solution Engineer, Product Engineer, Technical: Product Manager, Founding/Forward-Deployed Engineer, Implementation Consultant or a comparable technical, customer-facing role hybrid role.
What they're looking for
- Comprehensive knowledge of core operational workflows in supply chain and: procurement. You can speak the language of C-suite executives and seamlessly connect complex, systemic bottlenecks to strategic AI solutions.
- A track record of building coherent solutions, not just isolated features.: You think in terms of the whole solution and how the pieces fit together.
- Expert in data analysis and data modeling including tools native to the: Celonis platform: SQL, Python, quick to pick up new tools and platforms and able to prototype and build. Experience with platform-native tools like PQL is a significant asset.
- Advanced architectural mastery of LLM orchestration, tool use/function: calling, RAG, agents, prompt engineering, and agentic patterns for enterprise workflows.
