Applied Value Engineer- CPGR/CMT-NAM

The Role

As an Applied Value Engineer you are pushing the envelope in solving business-critical problems for our customers. You will be working with our most strategic customers, understanding their objectives and key challenges, and building Celonis solutions using the world’s leading Process Intelligence (PI) platform in combination with the largest AI and ML technology partners, such as Microsoft, OpenAI and Databricks.

Responsibilities

• AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. Find the best problem-solution fit and translate customer requirements into innovative solutions.
• Hackathons & Prototyping: Rapidly build creative prototypes (LLM/Agent-based) to solve business-critical problems during customer hackathons.
• Agentic Process Transformation: Enable a fundamental shift for our customers from traditional automation to autonomous AI agents empowered by the Celonis PI Platform.
• Proof Projects: Execute end-to-end Proof-of-Value (PoV) projects, ensuring compliance with enterprise data and identity frameworks.
• Identify & Frame Value: Discover and translate customers’ strategic priorities into high-impact Celonis use cases.
• Realize Value: Facilitate business value workshops and use Celonis to identify and qualify opportunities for process enhancement.
• Scale Value: Responsible for the end-to-end customer value journey, landing, expanding, adoption and renewing.

Qualifications

• Experience: 4+ years in an analytical role demonstrating value through business data analysis and process improvement.
• Technical Skills: Good knowledge of Business Software / SaaS applications (e.g. SAP/ Oracle), experience with RPA and/or BI Tools, and hands-on experience with Process Mining tools.
• Programming: Hands-on Python, AI building and consulting experience.
• Project Management: Experience in planning and managing project scopes, expectations and timelines.
• Communication: Excellent communication and presentation skills in English.

Nice to Have

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering.
• Working knowledge of tools in the LLM ecosystem such as LangChain, LlamaIndex, or other OSS packages.
• Experience in deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex).