Join us as a Custom Software Engineer, crafting innovative SAP applications and extensions optimized for HANA. This role focuses on building high-performance, production-ready solutions by merging deep ABAP on HANA expertise with advanced AI patterns. You'll leverage LLMs, tools, and retrieval mechanisms to create intelligent workflows within enterprise SAP systems without the need for training foundation models from scratch.

Deliver scalable, cloud-ready solutions that adhere to HANA pushdown principles and modern ABAP practices. This position is ideal for engineers passionate about creating governed AI capabilities that can reason, retrieve context, and assist or act within SAP environments, ensuring accuracy and enterprise safety.

Develop custom software solutions, coding and enhancing components across various systems. Design and implement ABAP solutions optimized for SAP HANA, utilizing pushdown principles to maximize in-database processing. Build modular, testable, and maintainable ABAP code following clean architecture practices. Model enterprise business entities using CDS semantics for both transactional and analytical consumption.

Construct AI-enabled SAP experiences by integrating ABAP services with LLM capabilities, including tool calling, retrieval grounding (RAG), and deterministic fallbacks. Implement automated tests to ensure regression coverage for performance and correctness, and establish evaluation harnesses for AI behaviors. Ensure observability through logs, metrics, and traces for production support and root-cause analysis. Integrate services with SAP and non-SAP ecosystems, collaborating across teams for end-to-end solution correctness.

A strong foundation in ABAP Development on HANA, including performance tuning, pushdown techniques, and efficient SQL access patterns, is essential. Proficiency with CDS views and modern data modeling practices, such as associations, annotations, and authorization concepts, is required. Experience with AMDP/SQLScript for performance-critical scenarios and controlled code pushdown is necessary.

Demonstrate solid software engineering discipline, including clean design principles, a testing mindset, CI/CD orientation, and a focus on production readiness. Exhibit AI native build capabilities, encompassing LLM integration, retrieval grounding, tool orchestration, evaluation loops, and establishing safety boundaries. A minimum of 3 years of experience is required, with a preference for candidates with 2-5 years of relevant background. Fifteen years of full-time education is mandatory.