Associate Applied (ai) Value Engineer - Orbit Program (madrid-based)

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

Celonis is seeking an Associate Applied (AI) Value Engineer for their Orbit Graduate program. This role involves working with strategic customers to understand their business challenges and build solutions using Celonis' Process Intelligence platform combined with AI/ML technologies like OpenAI and Databricks. The engineer will prototype solutions, demonstrate value to executives, and ensure successful implementation and adoption. The role requires a STEM degree, understanding of generative AI techniques (RAG, multi-agent orchestration, fine-tuning), and proficiency in Python and ML libraries.

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

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-facing
  • prototyping
  • AI solutions
  • enterprise software

Other signals

  • customer-facing
  • prototyping
  • AI solutions
  • enterprise software