Join our team as a Custom Software Engineer to design and develop cutting-edge software solutions. You will leverage modern frameworks and agile practices to build scalable, high-performing applications tailored to specific business needs. This role focuses on creating AI-native, HANA-optimized SAP applications and extensions.

We are seeking an engineer who can combine deep ABAP on HANA expertise with agentic AI patterns. The objective is to deliver robust, cloud-ready solutions using HANA pushdown principles, modern ABAP, and governed AI capabilities. These solutions will enable reasoning, context retrieval, and assistance within enterprise SAP workflows.

Architect and implement ABAP solutions optimized for SAP HANA, emphasizing pushdown principles and efficient data processing. Develop modular, testable, and maintainable code using clean architecture practices. Model enterprise business entities with CDS semantics to support various consumption needs and design reusable data artifacts.

Build AI-enabled SAP experiences by integrating ABAP services with LLM capabilities, including tool calling and retrieval-grounded outputs. Implement prompts, tool schemas, and context assembly strategies to enhance accuracy and enforce enterprise safety. Develop automated tests to ensure performance and correctness, and establish evaluation harnesses for AI behaviors.

Instrument services with comprehensive logging, metrics, and traces for production support. Design robust error handling mechanisms for enterprise flows and support incident response by hardening solutions based on observed failure patterns. Integrate ABAP on HANA services with diverse SAP and non-SAP ecosystems, collaborating with cross-functional teams for end-to-end solution delivery.

A minimum of 3 years of experience is required, with a strong focus on SAP ABAP Development for HANA, including performance tuning and pushdown techniques. Proficiency in CDS views, modern data modeling, AMDP/SQLScript, and solid software engineering discipline are essential.

Candidates must possess AI-native build capabilities, including experience with LLM integration, retrieval grounding, tool orchestration, evaluation loops, and establishing safety boundaries. A background in clean design, a testing mindset, CI/CD orientation, and a focus on production readiness are highly valued. Familiarity with OData, API lifecycle management, and contract-first development is also beneficial.