As a Custom Software Engineer, you will design, code, and enhance application components using modern frameworks and agile practices. Your focus will be on delivering scalable, high-performing solutions tailored to specific business needs, particularly within the SAP ecosystem.

This role is instrumental in building AI-native, cloud-ready SAP solutions on ABAP Cloud. You will combine deep ABAP and SAP platform expertise with agentic AI architectures, LLM tooling, and rapid experimentation. The position emphasizes designing, implementing, and scaling intelligent SAP applications that integrate ABAP Cloud with LLMs, retrieval pipelines, APIs, and enterprise systems, moving beyond simple automation towards autonomy.

Develop AI-native SAP applications by embedding LLM-driven intelligence into core business processes. Implement AI-enabled SAP extensions leveraging the RESTful ABAP Programming Model (RAP), event-driven patterns, and cloud-native architectures. Craft clean, testable ABAP code that integrates seamlessly with AI services and enterprise APIs. Integrate agentic workflows, including tools, planners, memory, orchestration, and evaluation loops, within SAP processes. Build and integrate retrieval pipelines (RAG) using both SAP and non-SAP data sources for contextual, grounded responses. Design and implement prompt templates, grounding strategies, fallback logic, and safety boundaries for enterprise SAP use cases. Develop evaluation frameworks and design guardrails for authorization, data privacy, action boundaries, and error handling. Ensure factuality, traceability, and explainability in AI-driven SAP workflows, and build observability into AI-enabled applications.

A minimum of 2-5 years of experience in software engineering is required, with a minimum of 3 years specifically in custom software development. Proficiency in SAP ABAP Cloud, including RAP, CDS, OData, and clean core principles, is essential. Hands-on experience integrating Large Language Models (LLMs) and AI services into applications is a must. Demonstrated experience building RAG pipelines, working with embeddings, and implementing contextual retrieval is necessary. Strong fundamentals in software engineering, encompassing design, testing, and CI/CD practices, are expected. An ability to translate complex business problems into effective AI-enabled SAP solutions is crucial. Full-time education spanning 15 years is a prerequisite for this role.