This role focuses on developing custom software solutions by designing, coding, and enhancing components across various systems and applications. Leveraging modern frameworks and agile practices, you will deliver scalable, high-performing solutions precisely tailored to specific business needs. The core objective is to build AI-native, HANA-optimized SAP applications and extensions.

This involves merging deep ABAP on HANA engineering with agentic AI patterns, including LLMs, tools, retrieval, and evaluation. The position emphasizes delivering production-grade solutions with high performance and cloud readiness, utilizing HANA pushdown principles, contemporary ABAP, and governed AI capabilities. These capabilities will enable systems to reason, retrieve context, and assist or act within enterprise SAP workflows without the need for training foundation models from scratch.

You will design and develop ABAP solutions optimized for SAP HANA, employing pushdown principles to minimize data movement and maximize in-database processing. Responsibilities include building efficient data models and access patterns using CDS views, associations, and annotations, as well as implementing performance-critical logic with AMDP/SQLScript. Developing modular, testable, and maintainable ABAP code aligned with clean architecture and enterprise SDLC is crucial.

This role also involves building services and APIs with modern paradigms like OData, ensuring stability and contract-first behavior. Modeling enterprise business entities using CDS semantics for transactional and analytical consumption, and designing reusable data artifacts for downstream consumers are key. Additionally, you will build AI-enabled SAP experiences by integrating ABAP services with LLM capabilities, including tool calling, retrieval grounding, and implementing robust evaluation loops and safety guardrails for AI outputs.

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

Solid software engineering discipline, encompassing clean design, a testing mindset, CI/CD orientation, and a focus on production readiness, is fundamental. Experience in AI-native development, including LLM integration, retrieval grounding, tool orchestration, evaluation loops, and establishing safety boundaries, is a primary requirement. A Bachelor's degree or equivalent in a related field is expected for this full-time position.