As a Custom Software Engineer, you will design, code, and enhance system components, leveraging modern frameworks and agile practices. The focus is on delivering scalable, high-performing solutions that precisely meet business requirements. This role involves building AI-native, HANA-optimized SAP applications by integrating deep ABAP on HANA engineering with agentic AI patterns. You will deliver production-grade solutions using HANA pushdown principles and governed AI capabilities.

Develop ABAP solutions optimized for SAP HANA, utilizing pushdown principles and efficient data models with CDS views. Implement performance-critical logic using AMDP/SQLScript. Write modular, testable, and maintainable ABAP code following clean architecture practices. Build services and APIs using modern paradigms like OData, ensuring stability and contract-first behavior. Model enterprise business entities with CDS semantics for transactional and analytical use. Create AI-enabled SAP experiences integrating ABAP services with LLM capabilities, including tool calling and retrieval grounding over SAP data. Implement prompts, tool schemas, and context assembly strategies to reduce hallucinations and enforce enterprise safety. Build automated tests for ABAP services and data artifacts. Establish evaluation harnesses for AI behaviors and introduce guardrails for AI outputs. 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. - ABAP on HANA Engineering - Modern ABAP Development & Clean Design - Data Modeling, Reporting & Semantic Enablement - AI Native SAP Capabilities - Quality Engineering & Evaluation Loops - Observability, Reliability & Operations - Integration & End to End Delivery

A minimum of 2-5 years of experience is required, with at least 3 years in SAP ABAP Development for HANA. Strong hands-on expertise in ABAP Development on HANA, including performance tuning, pushdown, and efficient SQL access patterns, is essential. Proficiency with CDS views and modern data modeling practices like associations, annotations, and authorization concepts is necessary. Experience with AMDP/SQLScript for performance-critical scenarios and controlled code pushdown is required. A solid software engineering discipline encompassing clean design, a testing mindset, CI/CD orientation, and production readiness is key. AI-native build capabilities, including LLM integration, retrieval grounding, tool orchestration, evaluation loops, and safety boundaries, are mandatory. OData/service design patterns, API lifecycle management, and contract-first development are strongly beneficial. Familiarity with performance benchmarking, load testing, and query-plan driven tuning practices is advantageous, as is knowledge of SAP security/authorizations and compliance requirements for sensitive enterprise data.