Join our team as a Custom Software Engineer, focusing on developing and enhancing SAP Production Planning (PP) solutions for discrete manufacturing environments. This role leverages AI-assisted development tools to streamline requirement analysis, configuration, testing, and issue resolution.

We aim to deliver efficient production planning, shop floor execution, and material staging processes. Integration of pre-built AI services is key to optimizing workflows, though no deep AI model engineering is required for this position.

Configure and support core SAP PP processes including Material Requirement Planning (MRP), Production Orders, Routings, BOM Management, Capacity Planning, Scheduling, Backflushing, Costing Integration, and Goods Movements.

Utilize AI copilots to accelerate functional specification creation, routing/BOM validation, test case generation, and documentation automation. Support the full delivery lifecycle from requirements to hypercare.

Integrate PP with other SAP modules (MM, QM, SD, FI/CO) and shop floor systems (MES). Employ AI tools for automated summarization of requirements, analysis of MRP exceptions, and faster defect isolation. Embed pre-built AI services for predictive insights and intelligent issue classification.

A strong foundation in SAP PP is essential, with a deep understanding of discrete manufacturing processes, BOM/routing management, production order cycles, capacity planning, scheduling, and MRP. Experience integrating PP with MM, QM, SD, and FI/CO is required.

Proficiency in using AI copilots, automated documentation tools, and AI-assisted test accelerators is necessary. Familiarity with embedding pre-built AI capabilities into production planning is expected, alongside an awareness of responsible AI usage.

Possess robust analytical and problem-solving skills, with the ability to translate manufacturing requirements into scalable SAP PP configurations. Excellent communication and collaboration skills are vital, along with a continuous learning mindset for adopting AI-assisted workflows. A minimum of 3 years of relevant experience and 15 years of full-time education are mandatory.