Shape the future of SAP solutions by building AI-native, cloud-ready applications on ABAP Cloud. This role integrates deep ABAP and SAP platform expertise with cutting-edge AI architectures, including Large Language Models (LLMs) and rapid experimentation.

You will be instrumental in designing, implementing, and scaling intelligent SAP applications. This involves seamlessly connecting ABAP Cloud with LLMs, retrieval-augmented generation (RAG) pipelines, APIs, and existing enterprise systems. The focus is on moving beyond mere automation towards true autonomy in enterprise workflows.

This is a hands-on role where you will actively build AI systems, not just utilize AI tools. The aim is to create intelligent SAP applications that can reason, retrieve information, and take action, fostering faster innovation cycles by embedding AI directly into SAP business logic.

Design and develop ABAP Cloud applications incorporating LLM-driven intelligence into core SAP business processes. Implement AI-enabled SAP extensions using modern approaches like RESTful ABAP Programming Model (RAP), event-driven patterns, and cloud-native architectures. Write clean, well-tested ABAP code that integrates smoothly with AI services and essential enterprise APIs. Integrate LLMs, embeddings, and RAG pipelines with ABAP Cloud services to deliver contextual and grounded responses. Build and integrate retrieval pipelines using both SAP and non-SAP data sources, including business objects, CDS views, documents, and events. Develop robust evaluation frameworks and design effective guardrails for authorization, data privacy, action boundaries, and error handling. Ensure the observability of AI-enabled SAP applications through telemetry, logging, and failure analysis. Rapidly prototype AI solutions, conduct frequent demonstrations, and iterate based on business feedback, while ensuring enterprise-grade performance, security, and compliance.

A strong foundation in SAP ABAP Cloud is essential, including proficiency with RAP, CDS, OData, and clean core principles. Demonstrated hands-on experience integrating LLMs and various AI services into applications is crucial. Proven experience in building RAG pipelines, implementing embeddings, and developing contextual retrieval mechanisms is required. Solid software engineering fundamentals, encompassing design principles, effective testing strategies, and CI/CD practices, are necessary. An ability to translate complex business problems into viable AI-enabled SAP solutions is key. A 15-year full-time education is a prerequisite for this role.