Applied Value Engineer - Production

Celonis is the global leader in Process Intelligence and the pioneer of Process Mining technology. As one of the world’s fastest-growing enterprise SaaS companies, we are changemakers pushing the boundaries of what’s possible. We invest heavily in advanced AI capabilities—specifically our Process Intelligence Graph—to turn data insights into immediate business action. We believe there is a massive opportunity to unlock global productivity and sustainability by placing intelligence at the core of every business process. Join our mission to make processes work for people, companies, and the planet. Role Description As a Senior Applied Value Engineer  you are pushing the envelope in solving business-critical problems for our strategic customers within our Production Vertical covering our Automotive, Manufacturing and Energy Vertical. . You will be working with our most strategic clients, understanding their unique strategic objectives—from Supply Chain Transformation, Warranty and Quality Management to supporting  large scale cost takeout programs —by  building 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.   With Celonis’ Process Intelligence (PI) platform, we feed operational context to AI so it understands our customers’ complex business realities (bridging IT and OT systems) and enables them to industrialize AI, unlocking real ROI on deployments at scale. You will prototype these solutions, demonstrate their value to Energy Executives, and ensure successful implementation, adoption, and value realization in order to increase the footprint of Celonis across the global energy landscape. Key Responsibilities: AI Discovery & Solutioning: Understand customers' AI strategy and sector-specific challenges (e.g., predictive maintenance, outage management, supply chain resilience, Quality Management). As a Celonis domain expert you are tasked to , find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle. Pre- and Post-Sales Execution: Actively drive the full customer lifecycle. Lead technical discovery and capability demonstrations during the pre-sales cycle, and remain deeply involved post-sale to guide implementation, ensuring agreed value and adoption thresholds are successfully reached. Hackathons & Prototyping: Think out of the box, have a „can-do“ attitude, and don’t shy away from complex operational problems. Leverage cutting-edge AI technologies to rapidly build creative prototypes in customer hackathons, solving critical pain points specific to Supply Chain, Manufacturing, Grid Operations and Warranty and Quality.. Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale, enabling a fundamental shift from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform (e.g., intelligent field service routing or autonomous procurement). Proof Projects: End-to-end execution of business-critical Proof-of-Value projects. This includes architecting and delivering secure, scalable LLM/agent systems with RAG, tools, and guardrails, while seamlessly integrating with enterprise data, identity protocols, and stringent energy compliance frameworks. Domain & Industry Leadership: Serve as the internal and external technical subject matter expert for the Energy vertical, scaling knowledge across the organization regarding utilities, upstream/downstream oil & gas, and renewable energy processes. Requirements: 4+ years of experience leading end-to-end technical pre-sales and post-sales engagements specifically within manufacturing and production. This includes defining AI roadmaps, building compelling ROI/TCO business cases, and guiding technical implementations through to value realization. Deep understanding of business processes native and industry knowledge in Energy and / or Manufacturing   with in-depth experience in domains such as Asset Management, Field Services, Supply Chain, Capital Projects, or Trading) with the ability to translate high-level business needs and strategic requirements into specific, impactful solutions Solid knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies relevant to handling large-scale industrial data. Strong presentation skills to both internal and external stakeholders (including C-level executives and operational leaders), whether leading technical whiteboarding sessions or formal readouts and demos. Bachelor’s Degree required; Master's Degree in computer science, engineering, mathematics, or related fields, or equivalent work experience preferred. Nice to have (big plus): Hands-on experience building agentic systems using LLM o