Lead Applied Value Engineer

The Role:

As Senior Applied Value Engineer, you are a strategic pioneer leading the charge in solving complex, 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 & Advanced AI Solutioning: Act as the foremost Celonis product and domain positioning expert. Seamlessly translate deep domain expertise and complex customer requirements into flawless enterprise architecture. You will lead technical discovery to architect, prototype, and build bespoke, state-of-the-art AI solutions targeting nuanced operational pain points.
• AI Solution Development: Lead the end-to-end execution of high-stakes Proof-of-Value (PoV) projects. Architect and deliver highly secure, scalable LLM/agent systems with advanced RAG, tools, and strict guardrails; integrating flawlessly with rigid enterprise data, identity, and compliance frameworks.
• Value Selling & Realization: Act as a trusted advisor, maintaining active involvement with strategic accounts to ensure programmatic value realization until agreed-upon value, massive adoption thresholds, and operational transformations are achieved.
• Domain & Industry Specialization: Leverage deep domain expertise combined with cross-system, AI-driven solutioning to architect industry-specific E2E solutions. You will codify this work into reusable methodology and globally scalable assets to accelerate time-to-value and mentor junior peers.

The qualifications you need:

• Executive-Facing Presales & Value Engineering (7+ years): Demonstrated experience independently owning the technical close and driving compelling AI transformation narratives. Requires a proven background in accountable PoV execution, complex ROI/TCO modeling, and showcasing the "Art of the Possible" by pitching visionary solutions to hidden problems—with a clear track record of driving projects all the way through to achieved value.
• Domain & Industry Expertise: Comprehensive knowledge of core operational workflows and industry landscapes (e.g., supply chain, finance). You can speak the language of C-suite executives and seamlessly connect complex, systemic bottlenecks to strategic AI solutions.
• Agentic AI Systems: Advanced architectural mastery of LLM orchestration, tool use/function calling, RAG, agents, prompt engineering, and agentic patterns for enterprise workflows.
• Math & Operations Research: Practical, expert-level application of linear/nonlinear optimization, rigorous statistical analysis, reinforcement learning, and advanced predictive forecasting.
• Production ML/LLMOps at Scale: Extensive experience in designing deployment architectures and dictating reliability standards for production-grade AI across cloud providers (AWS Bedrock, Azure AI, GCP Vertex AI).
• Software/Data Engineering: Python proficiency, modular API design, creating reusable libraries, advanced SQL, and scalable data integration using ML/AI frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face).
• AI Architecture & Security: Proven ability to architect secure enterprise cloud environments, ensuring stringent adherence to identity and access management (IAM) protocols, data governance frameworks, global privacy laws, and overarching security standards.
• 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 or related fields, or equivalent work experience preferred.