Lead Applied Value Engineer

As Senior Applied Value Engineer, you are a strategic pioneer leading the charge in solving complex, business-critical problems for our customers. Working with our most strategic global accounts, you will diagnose their strategy and key operational challenges to discover and build tailored, domain-specific use cases . You will architect and prototype state-of-the-art AI and technical solutions on the Celonis platform, demonstrate their business impact to C-suite Executives, and ensure successful implementation, adoption, and value realization.

• Executive-Facing Presales & Value Engineering (7+ years): Demonstrated experience independently owning the technical close and driving compelling AI transformation narratives. Requires a proven background in accountable PoV execution, complex ROI/TCO modeling, and showcasing the "Art of the Possible" by pitching visionary solutions to hidden problems—with a clear track record of driving projects all the way through to achieved value.
• Domain & Industry Expertise: Comprehensive knowledge of core operational workflows and industry landscapes (e.g., supply chain, finance). You can speak the language of C-suite executives and seamlessly connect complex, systemic bottlenecks to strategic AI solutions.
• Agentic AI Systems: Advanced architectural mastery of LLM orchestration, tool use/function calling, RAG, agents, prompt engineering, and agentic patterns for enterprise workflows.
• Math & Operations Research: Practical, expert-level application of linear/nonlinear optimization, rigorous statistical analysis, reinforcement learning, and advanced predictive forecasting.
• Production ML/LLMOps at Scale: Extensive experience in designing deployment architectures and dictating reliability standards for production-grade AI across cloud providers (AWS Bedrock, Azure AI, GCP Vertex AI).
• Software/Data Engineering: Python proficiency, modular API design, creating reusable libraries, advanced SQL, and scalable data integration using ML/AI frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face).
• AI Architecture & Security: Proven ability to architect secure enterprise cloud environments, ensuring stringent adherence to identity and access management (IAM) protocols, data governance frameworks, global privacy laws, and overarching security standards.
• Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos. Flawless English with exceptional executive presence.
• Degree: Masters Degree in computer science, engineering, mathematics or related fields, or equivalent work experience preferred.