Design and implement cutting-edge custom software solutions, meticulously coding and enhancing components across diverse systems. This role emphasizes leveraging modern frameworks and agile methodologies to deliver scalable, high-performing applications precisely tailored to unique business requirements.

The core focus is on building AI-native, HANA-optimized SAP applications. You will integrate deep ABAP on HANA engineering expertise with advanced agentic AI patterns, including Large Language Models (LLMs), tools, retrieval augmentation, and evaluation techniques. The objective is to produce production-grade solutions that are cloud-ready and operate with high performance.

Key to this role is the application of HANA pushdown principles, contemporary ABAP practices, and governed AI capabilities. These AI capabilities will enable systems to reason, retrieve context, and assist or act within enterprise SAP workflows, all without the need for training foundational models from scratch. This innovative approach ensures solutions are both powerful and secure.

Develop and optimize ABAP solutions for SAP HANA, prioritizing performance through pushdown techniques and maximizing in-database processing. Construct efficient data models and access patterns using CDS views, associations, annotations, and authorization concepts.

Implement modular, testable, and maintainable ABAP code following clean architecture principles and enterprise SDLC best practices. Build robust services and APIs using modern paradigms like OData, ensuring stability, versioning, and contract-first design.

Model enterprise business entities with CDS semantics for transactional and analytical use cases. Design reusable data artifacts to support various downstream consumers, including UI, integrations, analytics, and AI retrieval layers. Ensure clear business definitions and lineage-friendly structures for reduced ambiguity.

Integrate ABAP services with LLM capabilities to create AI-enabled SAP experiences. This includes orchestrating tool calling, grounding AI outputs using Retrieval Augmented Generation (RAG) over governed SAP data, and implementing deterministic fallbacks for low-confidence grounding.

Develop automated tests for ABAP services and data artifacts to ensure regression coverage for performance and correctness. Establish evaluation harnesses for AI behaviors, utilizing offline datasets, scenario-based tests, and online monitoring to detect drift. Introduce guardrails for AI outputs, such as authorization-aware context filtering, redaction rules, and action confirmations.

Possess strong hands-on expertise in ABAP Development on HANA, including performance tuning, pushdown optimization, and efficient SQL access patterns. Demonstrate proficiency with CDS views and modern data modeling techniques like associations, annotations, and authorization concepts.

Exhibit experience with AMDP/SQLScript for performance-critical scenarios and controlled code pushdown. Uphold solid software engineering discipline, emphasizing clean design, a testing mindset, CI/CD orientation, and production readiness.

Showcase AI-native build capabilities, including LLM integration, retrieval grounding, tool orchestration, evaluation loop implementation, and establishing safety boundaries. Familiarity with OData/service design patterns, API lifecycle management, and contract-first development is highly beneficial.

Experience integrating SAP backends with cloud runtimes and enterprise integration platforms is advantageous. Knowledge of SAP security, authorizations, and compliance requirements for sensitive enterprise data is also preferred. A 15-year full-time education is required.