Applied Value Engineer

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. World's leading companies trust Celonis and its global ecosystem of partners to make their AI agents, people, systems, and processes work together, achieving transformational outcomes. We believe there's a massive opportunity to unlock global productivity and sustainability by giving AI the context to understand how every business process really works. Join our mission to make processes work for people, companies, and the planet. Applied Value Engineer The Team:  As an Applied Value Engineer you push the envelope in solving mission-critical problems for our customers. You will work with our most strategic customers, understand their strategy and key challenges, and build Celonis solutions using cutting-edge AI technologies from market leaders such as Microsoft and OpenAI. With Celonis’ market-leading Process Intelligence (PI) Platform we feed operational context to AI so it understands our customers’ businesses and enables them to industrialize AI unlocking real ROI on AI deployments and at scale. There is no AI without PI. You will prototype these solutions, demonstrate their value to executives, and ensure successful implementation, adoption and value realization to increase Celonis' footprint at those customers. The Role: As an Applied Value Engineer, you are pushing the envelope, solving 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.  The work you’ll do: Discovery & AI Solutioning: Translate domain expertise, product knowledge, and specific customer requirements into flawless project execution. You will execute technical discovery, allowing you to prototype and build bespoke, state-of-the-art AI solutions that precisely target nuanced, industry-specific operational pain points. AI Solution Development: Drive the end-to-end execution of business-critical Proof-of-Value (PoV) projects. Deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrating with enterprise data, identity, and compliance frameworks. Value Selling & Realization: Maintain active technical and advisory involvement with strategic accounts, ensuring the project remains on track until agreed-upon value, adoption thresholds, and operational transformations are achieved. Domain & Industry Specialization: Leverage domain expertise to build industry-specific E2E solutions. Contribute to codifying this work into reusable methodology and assets to accelerate team-wide time-to-value. The qualifications you need: Executive-Facing Presales & Value Engineering (2+ years): Demonstrated experience supporting the technical close and driving compelling AI transformation narratives. Requires a proven background in accountable PoV execution, ROI/TCO modeling, and showcasing the "Art of the Possible" by pitching visionary solutions to hidden problems. Domain & Industry Expertise: Solid knowledge of core business processes and industry landscapes (e.g., supply chain, finance). Ability to speak the language of business leaders and connect operational bottlenecks to strategic AI solutions. Software/Data Engineering: Python proficiency, API design, SQL, data integration, and ML/AI libraries (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers). Agentic AI Systems: Hands-on experience with agentic AI setups including LLM orchestration, tool use/function calling, RAG, agents, prompt engineering, or agentic patterns for enterprise workflows. Production ML/LLMOps: Experience with model deployment, monitoring, MLOps/LLMOps, and lifecycle management across cloud services (AWS Bedrock, Azure AI, GCP Vertex AI). AI Architecture & Security: Understanding of cloud reference architectures, identity and access, data governance, privacy, and compliance. Math & Operations Research: Applied knowledge of linear/nonlinear optimization, statistical analysis, reinforcement learning, and forecasting is a plus. Strong presentation skills to both internal and external stakeholders (including executives), whether whiteboarding sessions or formal readouts and demos. Flawless English and native-level local language with exceptional executive presence. Degree: Master’s Degree in computer science, engineering, mathematics, business engineering, business information or related fields , or equivalent w