This role focuses on building AI-native, cloud-ready SAP solutions using ABAP Cloud. You'll combine deep ABAP and SAP platform expertise with agentic AI architectures and LLM tooling. The position involves designing, implementing, and scaling intelligent SAP applications that integrate ABAP Cloud with LLMs, retrieval pipelines, and enterprise systems, aiming for autonomy beyond mere automation.

This is a hands-on position where you'll actively build AI systems, not just utilize AI tools. The goal is to create intelligent SAP applications that can reason, retrieve information, and take action, driving faster innovation cycles and establishing a foundation for autonomous enterprise workflows.

Design and develop ABAP Cloud applications that embed LLM-driven intelligence into SAP business processes, using modern frameworks like the RESTful ABAP Programming Model (RAP). Implement AI-enabled SAP extensions with event-driven patterns and cloud-native architectures, ensuring clean, testable code. Integrate LLMs, embeddings, and retrieval-augmented generation (RAG) pipelines with SAP Cloud services, building agentic workflows with tools, planners, memory, and orchestration loops.

Construct retrieval pipelines using diverse SAP and non-SAP data sources, implementing chunking, indexing, and context assembly for production-grade RAG. Ensure factuality, traceability, and explainability in AI-driven SAP workflows. Implement evaluation frameworks and design guardrails for authorization, data privacy, and error handling. Build observability into AI-enabled applications for telemetry and failure analysis. Rapidly prototype, demo, and iterate on AI solutions, moving them into enterprise-grade production systems with a focus on performance, security, and compliance.

A minimum of three years of experience is required. The ideal candidate possesses strong software engineering fundamentals, including design, testing, and CI/CD practices. Essential skills include SAP ABAP Cloud (RAP, CDS, OData, clean core principles), alongside hands-on experience integrating LLMs and AI services into applications. Proficiency in building RAG pipelines, embeddings, and contextual retrieval mechanisms is crucial.

Additional beneficial skills include experience with SAP BTP, eventing, APIs, and cloud services. Familiarity with agent frameworks, custom orchestration logic, or exposure to vector databases and semantic indexing is advantageous. Knowledge of enterprise security, authorization, and compliance patterns is also highly valued. A background of 15 years of full-time education is a prerequisite.