This role focuses on developing advanced SAP applications and extensions, leveraging both deep ABAP on HANA expertise and AI patterns like LLMs and retrieval. The goal is to create high-performance, cloud-ready solutions using HANA pushdown techniques and modern ABAP. You will implement governed AI capabilities that enable reasoning, context retrieval, and assistance within enterprise SAP workflows.

The position does not involve training foundation models from scratch but rather building AI behaviors such as grounding, evaluation, and guardrails as integral parts of SAP solution delivery. This approach ensures faster delivery of intelligent SAP workflows with reduced operational risk.

Design and develop high-performance ABAP solutions for SAP HANA, emphasizing data pushdown principles and efficient data access using CDS views and AMDP/SQLScript.

Build modular, testable, and maintainable ABAP code following clean architecture practices, and develop services/APIs using modern paradigms like OData.

Model enterprise business entities with CDS semantics for transactional and analytical consumption, creating reusable data artifacts.

Develop AI-enabled SAP experiences by integrating ABAP services with LLM capabilities, including tool calling, retrieval-grounded outputs, and deterministic fallbacks.

Implement automated quality assurance through unit, integration, and contract tests, and establish evaluation harnesses for AI behaviors and guardrails.

Instrument services with logs, metrics, and traces for production support, design robust error handling, and support incident response.

Integrate ABAP on HANA services with SAP and non-SAP ecosystems, collaborating with cross-functional teams to ensure end-to-end solution correctness and performance.

A strong foundation in ABAP Development on HANA, including performance tuning, pushdown techniques, and efficient SQL access patterns, is essential.

Proficiency with CDS views, modern data modeling practices (associations, annotations, authorization concepts), and AMDP/SQLScript for performance-critical scenarios is required.

Solid software engineering discipline, including clean design, a testing mindset, CI/CD orientation, and a focus on production readiness, is crucial.

Experience in building AI-native capabilities such as LLM integration, retrieval grounding, tool orchestration, evaluation loops, and implementing safety boundaries is a key requirement.

Additional beneficial skills include OData/service design patterns, API lifecycle management, contract-first development, and familiarity with SAP security and authorization compliance.