Applied Value Engineer - CPGR/CMT-NAM

Responsibilities

• Understand customers’ AI strategies and business-critical challenges; identify problem-solution fit and translate requirements into innovative Celonis solutions.
• Rapidly build creative prototypes using AI technologies during customer hackathons.
• Enable customers to achieve ROI from AI deployments at scale by supporting the transition from rule-based automation to autonomous AI agents powered by the Celonis Process Intelligence Platform.
• Execute business-critical Proof-of-Value projects end to end, including architecture and delivery of secure, scalable LLM and agent systems with RAG, tools, and guardrails.
• Integrate solutions with enterprise data, identity, and compliance frameworks.
• Remain involved until agreed value and adoption thresholds are reached.
• Develop specialization in relevant domains or industries, such as supply chain or consumer packaged goods and retail.

Requirements

• 6+ years of experience leading technical pre-sales, including defining AI roadmaps, building ROI/TCO business cases, and prototyping machine learning and generative AI solutions.
• Experience in the consumer packaged goods and retail industry.
• Understanding of generative AI techniques, including RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, and fine-tuning.
• Understanding of business processes across sectors such as supply chain or finance, with the ability to translate business needs into specific AI use cases.
• Good knowledge of Python and common machine learning libraries, including LangChain, pandas, pydantic, scikit-learn, and PyTorch.
• Knowledge of data engineering tools and technologies.
• Strong presentation skills for internal and external stakeholders, including executives, whiteboarding sessions, formal readouts, and demos.
• Bachelor’s degree required.
• Master’s degree in computer science, engineering, mathematics, or a related field, or equivalent work experience preferred.

Nice to Have

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, with safety evaluations and guardrails.
• Experience with LLM ecosystem tools such as LangChain, LlamaIndex, or other open-source packages.
• Experience deploying and monitoring models at scale on AWS Bedrock, Azure AI, or Google Cloud Vertex AI.

Compensation and Benefits

• Restricted Stock Units and merit-based refresh grants for full-time employees.
• Inclusive parental leave: 24 weeks of fully paid leave for primary carers and 12 weeks for supporting carers.
• Unlimited PTO in applicable regions and generous PTO globally.
• Flexible hybrid work model.
• Learning and mentorship programs, including a 70-20-10 learning framework and dedicated learning platform.
• Subsidized Wellhub memberships, mental health counseling, and Wellness Weeks.
• Paid time off for community and environmental volunteering through annual Impact Days.
• Inclusion and belonging programs, including Inclusion Think Tank and Inclusion Days.