Senior Applied Value Engineer - EAM - NAM

Responsibilities

• Understand customers’ AI strategies and business-critical challenges, identify problem-solution fit, and translate requirements into innovative Celonis solutions.
• Build creative prototypes using AI technologies during customer hackathons.
• Enable agentic process transformation by helping customers achieve ROI from AI deployments at scale.
• 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 through project completion until agreed value and adoption thresholds are reached.
• Develop domain or industry specialization, including Energy and Oil & Gas.
• Present solutions to internal and external stakeholders, including executives, through whiteboarding sessions, formal readouts, and demonstrations.

Requirements

• 5+ 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 Energy, Oil & Gas industry.
• Understanding of generative AI techniques such as RAG, few-shot learning, prompt engineering, multi-agent orchestration, multimodal understanding, and fine-tuning.
• Understanding of business processes across sectors such as Supply Chain and Finance, with the ability to translate business needs into AI use cases.
• Good knowledge of Python and common machine-learning libraries and data-engineering technologies.
• Strong presentation skills for internal and external stakeholders, including executives.
• Bachelor’s degree required.
• Master’s degree in computer science, engineering, mathematics, or a related field, or equivalent work experience preferred.

Nice to Haves

• Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, with safety evaluations and guardrails.
• Working knowledge of 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.

Compensation and Benefits

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