This role focuses on building AI-native, HANA-optimized SAP applications and extensions. You will combine deep ABAP on HANA engineering with agentic AI patterns, including LLMs, tools, retrieval, and evaluation. The emphasis is on delivering high-performance, cloud-ready, production-grade solutions by leveraging HANA pushdown principles, modern ABAP, and governed AI capabilities.

Key to this position is the ability to develop solutions that can reason, retrieve context, and assist or act within enterprise SAP workflows, all without the need to train foundation models from scratch. This is an opportunity to work at the forefront of AI and SAP integration.

Develop high-performance ABAP solutions optimized for SAP HANA, employing pushdown principles and efficient data access patterns. Build modular, testable, and maintainable ABAP code using clean architecture practices and modern paradigms like OData. Model enterprise business entities using CDS semantics for transactional and analytical consumption.

Integrate ABAP services with LLM capabilities, focusing on tool calling orchestration, retrieval-grounded outputs (RAG), and deterministic fallbacks. Implement prompts, tool schemas, and context assembly strategies to minimize hallucinations and enforce enterprise safety boundaries. Develop automated tests for ABAP services and data artifacts, and establish evaluation harnesses for AI behaviors.

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 various teams to ensure end-to-end solution correctness. Rapidly prototype, demonstrate, and evolve solutions into scalable, secure, and compliant production systems.

A minimum of 3 years of experience is required. You must possess strong hands-on expertise in ABAP Development on HANA, including performance tuning, pushdown techniques, and efficient SQL access patterns. Proficiency with CDS views and modern data modeling practices is essential, along with experience in AMDP/SQLScript for performance-critical scenarios.

A solid software engineering discipline, encompassing clean design, a testing mindset, CI/CD orientation, and production readiness, is expected. Experience in building AI-native capabilities, such as LLM integration, retrieval grounding, tool orchestration, evaluation loops, and safety boundaries, is also a primary requirement.

Beneficial skills include OData/service design patterns, API lifecycle management, and integrating SAP backends with cloud runtimes. Familiarity with performance benchmarking, load testing, and SAP security/authorization concepts will further strengthen your profile.