Associate Applied (ai) Value Engineer (scale Emea/german-speaking) - Orbit Program

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

Celonis is seeking an Associate Applied AI Value Engineer for their Orbit Graduate program. This role focuses on understanding customer AI strategies, prototyping solutions using AI and ML technologies (like OpenAI, Databricks) integrated with Celonis' Process Intelligence platform, and demonstrating their business value. The role involves building prototypes, supporting agentic process transformation, executing proof-of-value projects, and presenting business impact to executives, with a goal of ensuring successful implementation and adoption of AI solutions.

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.
  • Confidence in presenting to diverse audiences

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

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

Other signals

  • industrialize AI
  • unlocking real ROI on AI deployments and at scale
  • autonomous AI agents
  • AI strategy