Develop cutting-edge custom software solutions, coding and enhancing components across various systems. This role leverages modern frameworks and agile methodologies to deliver scalable, high-performing applications precisely tailored to unique business requirements. Embrace AI native architectures and cloud-ready SAP solutions, integrating deep ABAP expertise with agentic AI and Large Language Models (LLMs) for rapid innovation.

The focus is on designing, implementing, and scaling intelligent SAP applications by merging ABAP Cloud capabilities with LLMs, retrieval pipelines, and enterprise systems. This position actively contributes to building AI systems, moving beyond simply using AI tools to creating autonomous, intelligent enterprise workflows.

Design and construct AI-native ABAP Cloud applications that embed LLM-driven intelligence into SAP business processes. Implement AI-enabled SAP extensions using the RESTful ABAP Programming Model (RAP), event-driven patterns, and cloud-native architectures. Write clean, testable ABAP code that integrates seamlessly with AI services and enterprise APIs.

Develop agentic workflows, incorporating tools, planners, memory, orchestration, and evaluation loops integrated with SAP processes. Integrate LLMs, embeddings, and retrieval-augmented generation (RAG) pipelines with ABAP Cloud services for contextually relevant and grounded responses. Craft prompt templates, grounding strategies, fallback logic, and safety boundaries suitable for enterprise SAP use cases.

Build and integrate retrieval pipelines using both SAP and non-SAP data sources, including business objects, CDS views, documents, and events. Implement chunking, indexing, embeddings, and context assembly to support production-grade RAG scenarios. Ensure factuality, traceability, and explainability in AI-driven SAP workflows.

Establish evaluation frameworks (offline and online) for AI behaviors integrated with SAP processes. Design robust guardrails for authorization, data privacy, action boundaries, and error handling. Integrate observability into AI-enabled SAP applications through telemetry, logging, and failure analysis.

Prototype rapidly, demo frequently, and iterate based on business feedback. Transition AI prototypes into enterprise-grade SAP production systems, prioritizing performance, security, and compliance. Continuously refine AI behavior, prompts, and orchestration strategies.

A strong foundation in SAP ABAP Cloud, including experience with RAP, CDS, OData, and clean core principles, is essential. Proven hands-on experience integrating LLMs and AI services into applications is required.

Demonstrated experience in building RAG pipelines, embeddings, and contextual retrieval mechanisms is necessary. Solid software engineering fundamentals, encompassing design, testing, and CI/CD practices, are expected. The ability to translate complex business problems into effective AI-enabled SAP solutions is critical.

Beneficial skills include experience with SAP BTP, eventing, APIs, and cloud services. Familiarity with agent frameworks or custom orchestration logic is advantageous. Exposure to vector databases, search, or semantic indexing, whether SAP-native or external, is strongly encouraged. Knowledge of enterprise security, authorization, and compliance patterns is also highly valued.