Develop custom software solutions by designing, coding, and enhancing components across various systems and applications. This role leverages modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

The focus is on building AI-native, HANA-optimized SAP applications and extensions. You'll combine deep ABAP on HANA engineering expertise with agentic AI patterns, including LLMs, tools, retrieval, and evaluation. The goal is to deliver production-grade solutions using HANA pushdown principles and modern ABAP capabilities, including governed AI functionalities.

Design and develop ABAP solutions optimized for SAP HANA, emphasizing pushdown principles and efficient data processing within the database. Build modular, testable, and maintainable ABAP code aligned with clean architecture practices and enterprise SDLC. Model enterprise business entities using CDS semantics to support transactional and analytical consumption, ensuring reusable data artifacts.

Integrate ABAP services with LLM capabilities, focusing on tool calling, retrieval-grounded outputs, and deterministic fallbacks. Implement automated tests for ABAP services and data artifacts, establishing evaluation harnesses for AI behaviors. Instrument services with logs, metrics, and traces for production support and integrate ABAP on HANA services with SAP and non-SAP ecosystems.

A minimum of 3 years of experience is required, with a strong foundation in SAP ABAP Development on HANA, including performance tuning and efficient SQL access patterns. Proficiency in CDS views, modern data modeling, and concepts like associations, annotations, and authorization is essential.

Experience with AMDP/SQLScript for performance-critical scenarios and controlled code pushdown is necessary. A solid software engineering discipline, including clean design, a testing mindset, CI/CD orientation, and production readiness, is expected. The role also requires AI-native build capabilities, such as LLM integration, retrieval grounding, tool orchestration, evaluation loops, and understanding safety boundaries.