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Celonis is seeking an Applied Value Engineer to work with strategic global accounts, diagnosing their operational challenges and architecting state-of-the-art AI solutions on the Celonis platform. You will translate domain expertise and customer requirements into flawless project execution, prototyping bespoke AI solutions that target industry-specific operational pain points.
Key responsibilities include:
**Discovery & AI Solutioning:** Execute technical discovery to prototype and build bespoke, state-of-the-art AI solutions targeting nuanced, industry-specific operational challenges. Translate domain expertise, product knowledge, and customer requirements into actionable technical strategies.
**AI Solution Development:** Drive end-to-end execution of business-critical Proof-of-Value (PoV) projects. Deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails; integrate with enterprise data, identity, and compliance frameworks.
**Value Selling & Realization:** Maintain active technical and advisory involvement with strategic accounts, ensuring projects remain on track until agreed-upon value, adoption thresholds, and operational transformations are achieved.
**Domain & Industry Specialization:** Leverage domain expertise to build industry-specific end-to-end solutions. Contribute to codifying work into reusable methodology and assets to accelerate team-wide time-to-value.
You will work with C-suite executives, demonstrating business impact and ensuring successful implementation and adoption. The role combines presales, value engineering, technical architecture, and hands-on AI development.
**Requirements:**
- Executive-facing presales and value engineering experience (2+ years): Demonstrated background in accountable PoV execution, ROI/TCO modeling, and pitching visionary solutions to hidden problems
- Domain and industry expertise: Solid knowledge of core business processes and industry landscapes (e.g., supply chain, finance); ability to 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 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 (preferred)
- Strong presentation skills to internal and external stakeholders including executives; flawless English with exceptional executive presence; Dutch fluency preferred but not essential
- Master's degree in computer science, engineering, mathematics, business engineering, business information, or related fields; or equivalent work experience
