Applied Value Engineer
Pubblicato il 07-09-2026 - NextGenEnergyJobs in Milano
As an Applied Value Engineer you push the envelope in solving mission-critical problems for our customers.
Key Responsibilities
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.
Requirements
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 work experience preferred.
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