Join our team as a Custom Software Engineer, focusing on developing and enhancing SAP Materials Management (MM) processes. You will leverage AI-assisted development tools to streamline requirement analysis, configuration, testing, and problem resolution.

This role emphasizes integrating pre-built AI capabilities to boost productivity in procurement, inventory management, and supplier collaboration, without requiring deep LLM development expertise. Contribute to building scalable, high-performing solutions tailored to specific business needs using modern frameworks and agile practices.

Configure and optimize SAP MM processes including Procure to Pay (P2P), Purchase Requisition/Order Management, Source List & Quota Arrangements, Vendor Management, Inventory Management, Material Master Data, and Release Strategies.

Utilize AI copilots for generating functional specifications, validating configuration, creating test cases, and automating documentation. Support end-to-end delivery from requirements gathering to hypercare, integrating MM with other SAP modules (SD, FI, PP, QM) and external systems.

Apply AI tools to accelerate requirement interpretation, data validation, error diagnostics, test creation, and document generation. Integrate pre-built AI services for automated material classification, predictive signals, and intelligent summarization of exceptions. Employ LLM assisted troubleshooting to reduce incident resolution times.

A strong understanding of SAP MM, including P2P processes, purchasing document flows, vendor evaluation, and inventory management is essential. Experience in configuring material master, vendor master, PO/PR processing, goods movements, and release strategies is required.

Familiarity with integration across SAP SD, FI, PP, and QM, as well as knowledge of IDocs, outputs, pricing procedures, and common MM troubleshooting patterns are expected.

Demonstrated hands-on experience with AI copilots, LLM powered documentation tools, and AI assisted testing accelerators is crucial. You should be able to integrate pre-built AI capabilities into MM workflows for automation and insight generation. Strong analytical, problem-solving, and clear communication skills are necessary, along with a continuous learning mindset for adopting AI-enabled productivity tools.