Applied Value Engineer

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 with exceptional executive presence.
• Degree: Masters Degree in computer science, engineering, mathematics, business engineering, business information or related fields , or equivalent work experience preferred.

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