Applied Value Engineer

Responsibilities

• Diagnose strategic and operational challenges for global enterprise customers and identify tailored, domain-specific AI use cases.
• Conduct technical discovery and prototype bespoke AI solutions on the Celonis platform.
• Drive end-to-end Proof-of-Value projects, delivering secure and scalable LLM and agent systems with retrieval-augmented generation, tools, and guardrails.
• Integrate AI solutions with enterprise data, identity, and compliance frameworks.
• Support technical sales cycles, present AI transformation narratives, and demonstrate business impact to C-suite executives.
• Model ROI and total cost of ownership and maintain technical and advisory involvement through adoption and value realization.
• Build industry-specific solutions and codify reusable methodologies and assets.

Requirements

• 2+ years of experience in executive-facing presales or value engineering, including technical closing, accountable Proof-of-Value execution, ROI/TCO modeling, and executive presentations.
• Domain expertise in core business processes and industry landscapes such as supply chain or finance.
• Proficiency in Python, API design, SQL, data integration, and machine learning or AI libraries.
• Hands-on experience with agentic AI, LLM orchestration, tool use or function calling, retrieval-augmented generation, prompt engineering, or enterprise agentic patterns.
• Experience with model deployment, monitoring, MLOps/LLMOps, and lifecycle management across cloud AI services.
• Understanding of cloud architectures, identity and access management, data governance, privacy, and compliance.
• Strong presentation and executive communication skills.
• Fluent English with exceptional executive presence.
• Master's degree in computer science, engineering, mathematics, business engineering, business information, or a related field, or equivalent experience preferred.

Nice-to-haves

• Applied knowledge of linear and nonlinear optimization, statistical analysis, reinforcement learning, or forecasting.
• Experience with PyTorch, TensorFlow, scikit-learn, XGBoost, Hugging Face Transformers, AWS Bedrock, Azure AI, or Google Cloud Vertex AI.

Compensation and Benefits

• Restricted Stock Units and merit-based refresh grants for full-time employees.
• Flexible hybrid work model.
• Paid parental leave, paid time off, learning and mentorship programs, Wellhub membership subsidies, mental health counseling, wellness initiatives, and paid volunteer time.