Spearhead the development of custom software solutions, focusing on designing, coding, and enhancing components across diverse systems and applications. Leverage modern frameworks and agile methodologies to deliver scalable, high-performance solutions precisely tailored to unique business requirements.

This role emphasizes designing, configuring, and enhancing SAP Production Planning (PP) processes within discrete manufacturing settings. You will utilize AI-assisted development tools and copilots to accelerate various stages, including requirement analysis, configuration, testing, documentation, and issue resolution. The primary focus is on optimizing production planning, shop floor execution, and material staging processes, with opportunities to integrate pre-built AI services where advantageous. Please note that extensive AI model engineering, vector database work, RAG, or agentic system development is not expected.

Configure and provide robust support for SAP PP processes, encompassing Material Requirement Planning (MRP), Production Orders & Execution, Routings, Work Centers & BOM Management, Capacity Planning & Scheduling, Backflushing & Costing Integration, and Goods Movements & Shop Floor Reporting.

Utilize AI copilots to streamline the creation of functional specifications, validation of routings/BOMs, generation of test cases for MRP and order creation, and automation of documentation (FS/TS/SOPs).

Support the entire project lifecycle, from requirements gathering and design through configuration, SIT/UAT, deployment, and hypercare support. Ensure seamless integration of PP with MM, QM, SD, FI/CO, and shop floor systems (MES) by leveraging standard APIs and middleware.

Employ AI copilots for automated summarization of requirements and change impacts, analysis of MRP exceptions and planning alerts, validation of order execution and production variances, and faster defect isolation in configurations. Integrate pre-built AI services into production workflows for predictive insights, intelligent classification of production issues, automated summarization of batch deviations, and smart suggestions based on historical performance. Employ LLM-assisted troubleshooting to reduce time spent analyzing MRP exceptions, order failures, and material shortages.

Maintain compliance with production governance, change controls, data accuracy standards, and audit policies. Actively participate in workshops, solution reviews, and process optimization discussions, enhanced by AI-generated insights. Collaborate effectively with production, quality, warehouse, procurement, cost controlling, and integration teams to achieve end-to-end planning excellence. Develop reusable templates, checklists, test packs, and AI-enabled best practices for SAP PP delivery.

Possess strong SAP PP expertise, including a deep understanding of discrete manufacturing processes such as BOM/routing management, production order cycles, capacity planning, scheduling, and MRP. Demonstrate experience with integrations across MM (material availability), QM (inspection lots), SD (demand), and FI/CO (costing). Familiarity with order confirmations, settlements, and shop floor data capture processes is essential.

Exhibit AI-ready skills, enabling you to effectively use AI copilots, automated documentation tools, and AI-assisted test accelerators. You should be comfortable embedding pre-built AI capabilities into production planning or execution, without the need for custom model building. Maintain an awareness of responsible AI usage and its limitations within manufacturing and planning environments.

Demonstrate general professional skills including strong analytical and problem-solving abilities related to production variability, MRP outcomes, and resource planning. Be adept at translating manufacturing requirements into scalable SAP PP configurations. Possess excellent communication and collaboration skills, effective across both technical and operational teams. Cultivate a continuous learning mindset, embracing AI-assisted workflows.

A minimum of 3 years of experience is required, with a preference for candidates with 2-5 years of relevant experience. A 15-year full-time education is mandatory for this role.