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Forward Deployed Engineer (AI) - Production Systems (a) 100%

Geberit International AG

Rapperswil-Jona · On-site Mid Level 4w ago

About the role

About

The globally operating Geberit Group is the European market leader for sanitary products and employs 11,000 people in over 50 countries. The Group headquarters are located in Rapperswil-Jona, Switzerland.

Main Tasks

The Forward Deployed Engineer (AI) is part of the AI Competence Center (AICC)—the company’s central hub for applied AI expertise, standards, and enablement. This role is responsible for developing, validating, and operationalizing AI solutions for the company’s production environments. The role spans the full lifecycle of applied AI use cases - starting with rapid prototyping and proof-of-concept implementations and extending through the transition to production‑ready, scalable, and compliant systems.

  • Rapidly design and implement AI prototypes and proof-of-concept solutions for manufacturing and operational use cases (e.g., quality inspection, process optimization, predictive maintenance)
  • Collaborate with domain experts and production teams to validate feasibility, value, and constraints of AI approaches in real‑world settings
  • Evaluate data availability, data quality, and technical readiness for scaling prototypes beyond experimentation
  • Lead and support the transition of validated AI prototypes into production‑ready systems
  • Act as a technical bridge between the AI Competence Center and production sites or operational units
  • Build and maintain production‑grade AI services, data pipelines, and APIs
  • Implement monitoring, logging, and alerting for AI systems, covering performance, data quality, and model behavior
  • Apply responsible AI principles and internal governance requirements from early prototyping through production deployment
  • Contribute reusable components, architectural patterns, and lessons learned back to the AI Competence Center to enable scaling across the organization

Education and Qualification

  • Strong software engineering experience (e.g., Python, HTML/CSS, Javascript, TypeScript)
  • Industrial plc / data aquisition technologies experience (Siemens S7, OPC‑UA, Modbus)
  • Experience in deploying AI or data‑driven systems in production environments
  • Practical knowledge of: Machine learning and/or LLM‑based systems, data pipelines and integration with enterprise systems, APIs, containerized applications and microservices
  • Experience working in or close to manufacturing, industrial, or operational environments
  • Ability to work hands‑on in production contexts while maintaining a reusable, strategic mindset via the AICC
  • Strong communication skills across technical and non‑technical stakeholders
  • Pragmatic, solution‑oriented approach with a strong sense of ownership.

Additional Information

We only consider direct applications for this position.

Requirements

  • Strong software engineering experience
  • Industrial plc / data aquisition technologies experience
  • Experience in deploying AI or data-driven systems in production environments
  • Practical knowledge of: Machine learning and/or LLM-based systems, data pipelines and integration with enterprise systems, APIs, containerized applications and microservices
  • Experience working in or close to manufacturing, industrial, or operational environments
  • Ability to work hands-on in production contexts while maintaining a reusable, strategic mindset via the AICC
  • Strong communication skills across technical and non-technical stakeholders
  • Pragmatic, solution-oriented approach with a strong sense of ownership

Responsibilities

  • Rapidly design and implement AI prototypes and proof-of-concept solutions for manufacturing and operational use cases
  • Collaborate with domain experts and production teams to validate feasibility, value, and constraints of AI approaches in real-world settings
  • Evaluate data availability, data quality, and technical readiness for scaling prototypes beyond experimentation
  • Lead and support the transition of validated AI prototypes into production-ready systems
  • Act as a technical bridge between the AI Competence Center and production sites or operational units
  • Build and maintain production-grade AI services, data pipelines, and APIs
  • Implement monitoring, logging, and alerting for AI systems, covering performance, data quality, and model behavior
  • Apply responsible AI principles and internal governance requirements from early prototyping through production deployment
  • Contribute reusable components, architectural patterns, and lessons learned back to the AI Competence Center to enable scaling across the organization

Skills

APIHTML/CSSJavascriptLLMMachine learningMicroservicesModbusOPC-UAPythonSiemens S7TypeScript

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