Open roleExternal
Applied Value Engineer
- london, england, United Kingdom
- Permanent·On-site
- Full time
- £90 - £130 Per Hour
Job Description
At Celonis, we believe our people make us who we are and that “The Best Team Wins”.
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 with exceptional executive presence.
- Degree: Masters Degree in computer science, engineering, mathematics, business engineering, business information or related fields , or equivalent work experience preferred.