Associate Applied (ai) Value Engineer (benelux) - Orbit Program

Celonis Celonis · Data AI · Madrid, Spain · Value Engineering

The Associate Applied (AI) Value Engineer will work with enterprise customers to understand their business challenges and build Celonis solutions using AI/ML technologies, focusing on agentic process transformation and prototyping AI solutions. This role involves customer interaction, solution design, and demonstrating business value.

What you'd actually do

  1. AI Discovery & Solutioning: Understand customers AI strategy and business critical challenges. As Celonis product & domain expert, find the best problem-solution fit and translate customer requirements into innovative solutions that move the needle
  2. Hackathons & Prototyping: Think out of the box, have a “can-do“ attitude and don’t shy away from complex problems. Leverage cutting edge AI technologies to rapidly build creative prototypes in customer hackathons solving business critical problems
  3. Agentic Process Transformation: Support our customers in achieving real ROI out of AI deployments at scale enabling a fundamental shift in business operations from traditional, rule-based automation to the use of autonomous AI agents empowered by our Celonis Process Intelligence Platform
  4. Proof Projects: End-to-end execution of business-critical Proof-of-Value projects showcasing the value of Celonis Process Intelligence tailored to customers and align our solutions with their AI strategy.
  5. Business Impact Presentations: Articulate and quantify strategic business value for customers, delivering impactful presentations to senior executives to ensure successful value realization for customers.

Skills

Required

  • Degree in Engineering, Data Analytics/Science, Computer Science, Mathematics, or a related STEM field.
  • Understanding of generative AI techniques like RAG, few shot learning, prompt/context engineering, multi-agent orchestration, multimodal understanding, or fine-tuning that are used to build high-impact use cases like intelligent chatbots and automated text processors.
  • Good knowledge of Python and common ML libraries (such as LangChain, pandas, pydantic, sklearn, PyTorch) as well as data engineering tools and technologies.
  • Excellent analytical and creative problem-solving skills, with the ability to apply technology to business challenges.
  • A customer-centric mindset with a focus on delivering value.

Nice to have

  • Extensive internship experience or 1-2 years of full-time work experience. Ideally at the intersection of business and technology.

What the JD emphasized

  • customer hackathons
  • autonomous AI agents
  • AI deployments at scale
  • AI strategy

Other signals

  • customer-facing
  • prototyping
  • AI agents
  • enterprise SaaS