This role involves developing cutting-edge, AI-native SAP applications and extensions, specifically optimized for HANA. You will combine deep ABAP on HANA engineering expertise with modern agentic AI patterns, including LLMs, tools, and retrieval augmented generation. The focus is on delivering high-performance, cloud-ready, production-grade solutions that leverage HANA pushdown principles and governed AI capabilities.

The position emphasizes building solutions that can reason, retrieve context, and assist or act within enterprise SAP workflows without the need for training foundation models from scratch. This is an opportunity to work on innovative technology that transforms how businesses operate.

Design and develop ABAP solutions optimized for SAP HANA, focusing on pushdown principles to maximize in-database processing and minimize data movement. Build efficient data models and access patterns using CDS views, associations, and authorization concepts. Implement performance-critical logic using AMDP/SQLScript when appropriate, adhering to strict governance and testing protocols.

Develop modular, testable, and maintainable ABAP code aligned with clean architecture practices. Build robust services and APIs using modern paradigms like OData, ensuring stability and contract-first behavior. Consistently apply secure coding standards and authorization checks across all layers.

Model enterprise business entities using CDS semantics for both transactional and analytical consumption. Design reusable data artifacts that support various downstream consumers. Ensure lineage-friendly structures and consistent business definitions for clarity across systems.

Build AI-enabled SAP experiences by integrating ABAP services with LLM capabilities. This includes orchestrating tool calling, implementing retrieval-grounded outputs over governed SAP data, and establishing deterministic fallbacks when grounding is weak. Implement prompts, tool schemas, and context assembly strategies to reduce hallucinations and enforce enterprise safety boundaries.

Develop automated tests (unit, integration, contract) for ABAP services and data artifacts. Establish evaluation harnesses for AI behaviors using golden datasets, scenario-based tests, and online monitoring. Introduce guardrails for AI outputs, including authorization-aware filtering, redaction rules, action confirmations, and audit logs.

Instrument services with logs, metrics, and traces for production support and root-cause analysis. Design robust error handling for enterprise flows with retries, idempotency, and correlation IDs. Support incident response with runbooks and continuous hardening of solutions.

Integrate ABAP on HANA services with SAP and non-SAP ecosystems. Collaborate with UX, integration, data, and platform teams to ensure end-to-end solution correctness and performance. Rapidly prototype, demonstrate solutions frequently, and evolve prototypes into scalable production systems with security and compliance integrated from the start.

A minimum of 3 years of experience is required for this role, with a preference for 2-5 years. Essential technical skills include strong hands-on expertise in ABAP Development on HANA, with a focus on performance tuning, pushdown techniques, and efficient SQL access patterns. Proficiency with CDS views and modern data modeling practices such as associations, annotations, and authorization concepts is crucial.

Experience with AMDP/SQLScript for performance-critical scenarios and controlled code pushdown is expected. A solid software engineering discipline, encompassing clean design principles, a strong testing mindset, CI/CD orientation, and a commitment to production readiness, is vital. Furthermore, capabilities in AI-native development are required, including LLM integration, retrieval grounding, tool orchestration, evaluation loops, and establishing safety boundaries.

Beneficial skills include proficiency in OData/service design patterns, API lifecycle management, and contract-first development. Experience integrating SAP backends with cloud runtimes and enterprise integration platforms is advantageous. Familiarity with performance benchmarking, load testing, and query-plan driven tuning practices is also a plus. A good understanding of SAP security, authorizations, and compliance requirements for sensitive enterprise data would be highly valued.