Associate Applied (ai) Value Engineer (dach)

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

Celonis is seeking an Associate Applied (AI) Value Engineer to work with strategic customers, understanding their business objectives and challenges, and building Celonis solutions using their Process Intelligence platform combined with AI/ML partners like Microsoft and OpenAI. The role involves prototyping AI solutions, demonstrating their value to executives, and ensuring successful implementation and adoption. The role is part of the Orbit Graduate program, offering a blend of client engagements, mentorship, and training in AI solutioning, platform building, and value selling.

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 base will be in Germany/DACH area
  • customer hackathons
  • customer accounts
  • customer-centric mindset

Other signals

  • customer-facing
  • prototyping
  • AI agents
  • process intelligence