Develop innovative custom software solutions by designing, coding, and enhancing system components. Employ modern frameworks and agile methodologies to deliver scalable, high-performance applications precisely tailored to unique business requirements.

This role emphasizes leveraging AI-assisted development tools and copilots to expedite tasks such as requirement analysis, configuration, testing, documentation, and issue resolution. The focus is on optimizing procurement, inventory management, and supplier collaboration through the integration of pre-built AI capabilities, without requiring in-depth LLM development expertise.

Configure and refine SAP Materials Management (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 to generate functional specifications, validate configuration logic, create comprehensive test cases, and automate key documentation. Support end-to-end project delivery, from requirements gathering and solution design to configuration, testing, deployment, and hypercare.

Integrate MM modules with SD, FI, PP, QM, and external systems using standard APIs, IDocs, and middleware. Apply AI tools to accelerate requirement interpretation, process design, data validation, error diagnostics, test creation, and document generation. Enhance MM operations by integrating pre-built AI services for tasks like automated material classification or predictive signals for inventory management. Leverage LLM-assisted troubleshooting to minimize incident resolution times.

Possess strong expertise in SAP MM, including a deep understanding of P2P processes, purchasing document flows, vendor evaluation, and inventory management. Demonstrate experience in configuring material master, vendor master, PO/PR processing, goods movements, and release strategies.

Familiarity with integrations across SD, FI, PP, and QM is essential. Knowledge of IDocs, outputs, pricing procedures, and common MM troubleshooting patterns is required. Hands-on experience with AI copilots, LLM-powered documentation tools, and AI-assisted testing accelerators is crucial.

Ability to integrate pre-built AI capabilities into MM workflows for automation and insight generation. Understanding of responsible AI usage and data quality impacts is important. Strong analytical and problem-solving skills, coupled with the ability to translate business needs into scalable SAP MM configurations, are necessary. Excellent communication and collaboration skills across functional business teams, along with a continuous learning mindset for adopting AI-enabled productivity tools, are highly valued.