Drive innovation as a Custom Software Engineer, crafting AI-native, HANA-optimized SAP applications and extensions. This role merges deep ABAP on HANA expertise with advanced AI patterns, including LLMs, tools, retrieval, and evaluation. Focus on delivering high-performance, cloud-ready, production-grade solutions utilizing HANA pushdown principles and modern ABAP capabilities.

Contribute to enterprise SAP workflows by implementing AI capabilities that can reason, retrieve context, and assist or act autonomously. The position emphasizes grounded AI, leveraging existing enterprise SAP data and documentation without requiring foundational model training from scratch.

Design and develop high-performance ABAP solutions optimized for SAP HANA through effective pushdown principles and efficient data modeling with CDS views.

Build modular, testable, and maintainable ABAP code using modern paradigms like OData and APIs, adhering to secure coding standards.

Model enterprise business entities using CDS semantics and design reusable data artifacts for various consumers, ensuring consistent business definitions.

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

Implement prompts, tool schemas, and context assembly strategies to minimize hallucinations and enforce enterprise safety boundaries.

Build automated tests and establish evaluation harnesses for AI behaviors to ensure performance, correctness, and detect regressions.

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

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

A minimum of 3 years of experience in SAP ABAP Development for HANA, with a strong focus on performance tuning and pushdown techniques.

Proficiency in CDS views, modern data modeling practices, and AMDP/SQLScript for performance-critical scenarios.

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

Demonstrated experience in building AI-native capabilities such as LLM integration, retrieval grounding, tool orchestration, evaluation loops, and safety boundaries.

Experience with OData/service design patterns, API lifecycle management, and contract-first development is highly beneficial.

Familiarity with performance benchmarking, load testing, and SAP security/authorization concepts is advantageous.