AI & Process Excellence Intern: Supply Chain Analytics

Henkel AG & Co. KGaA

Amsterdam

On-site

EUR 70,000 - 110,000

Full time

2 days ago
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Job summary

Henkel AG & Co. KGaA in Amsterdam is seeking a hands-on AI Solution Architect to design and build intelligent supply chain agents using Microsoft Copilot Studio.

You will gather requirements from global and regional teams and translate them into impactful AI solutions that drive automation and faster decision-making. You will explore Databricks-powered agent capabilities, connect them with the Copilot ecosystem, and develop RAG-based assistants.

Responsibilities

  • Build AI Solutions for supply chain processes.
  • Design and develop Supply Chain AI agents using Microsoft Copilot Studio.
  • Gather requirements from global and regional business teams and translate them into AI solutions.
  • Build and improve RAG-based and task-oriented AI assistants to automate work and accelerate decision-making.
  • Explore emerging technologies and investigate Agentic AI with Databricks.
  • Evaluate how Databricks can connect with the Microsoft Copilot ecosystem.
  • Experiment with new technologies and turn ideas into proof-of-concepts.
  • Drive data-driven insights by supporting Celonis dashboards and process mining initiatives.
  • Create process maps and documentation for key business processes.
  • Support continuous improvement and digital transformation projects.
  • Grow a global community of Celonis users with training materials and adoption campaigns.
  • Organize community sessions to drive learning, collaboration, and innovation.

Job description

Henkel AG & Co. KGaA in Amsterdam is seeking a hands-on AI Solution Architect to design and build intelligent supply chain agents using Microsoft Copilot Studio.

You will gather requirements from global and regional teams and translate them into impactful AI solutions that drive automation and faster decision-making. You will explore Databricks-powered agent capabilities, connect them with the Copilot ecosystem, and develop RAG-based assistants.

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