Join our team as a Custom Software Engineer and drive the development of innovative SAP Materials Management (MM) solutions. You will leverage cutting-edge AI-assisted development tools, including copilots, to streamline requirement analysis, configuration, testing, and problem resolution. This role focuses on optimizing procurement, inventory management, and supplier collaboration through pre-built AI capabilities, enhancing productivity without deep AI model development.

This position is ideal for professionals seeking to integrate advanced technology into core business processes and contribute to a more efficient and data-driven procurement landscape.

Configure and enhance SAP MM processes such as Procure-to-Pay (P2P), vendor management, and inventory control. Utilize AI copilots to generate functional specifications, validate configurations, create test cases, and automate documentation. Support the end-to-end delivery lifecycle 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, and test creation. Leverage pre-built AI services for automated material classification, predictive insights (e.g., low stock), and intelligent exception handling. Employ LLM-assisted troubleshooting to minimize incident resolution times and ensure adherence to procurement governance and quality standards.

A strong foundation in SAP MM is essential, including deep understanding of P2P processes, vendor evaluation, and inventory management. Experience in configuring material master, vendor master, PO/PR processing, and release strategies is required. Familiarity with cross-module integration (SD, FI, PP, QM) and common MM troubleshooting patterns is expected.

Proficiency in using AI copilots, LLM-powered documentation tools, and AI-assisted testing accelerators is a must. The ability to integrate pre-built AI capabilities into MM workflows for automation and insight generation is key. Candidates should possess strong analytical and problem-solving skills, clear communication abilities, and a commitment to continuous learning and adopting AI-enabled tools.