Innovate by building AI-native enterprise applications on SAP Business Technology Platform (SAP BTP). This role blends strong platform engineering skills—encompassing administration, solution design, and full-stack development—with advanced agentic AI application patterns, including LLMs, tools, retrieval, and evaluation.

Your focus will be on developing, deploying, and managing cloud applications within SAP BTP, transforming them into intelligent systems through rapid prototyping and robust production hardening.

Develop and deploy custom software solutions, coding and enhancing components across various systems and applications using modern frameworks and agile practices.

Build, deploy, and manage cloud applications on SAP BTP, covering platform administration, solution design, and full-stack development.

Implement backend services and APIs with Node.js and expose them for frontend consumption. Develop responsive UIs using SAPUI5, integrating with backend APIs.

Design database artifacts, data models, and connect applications to SAP HANA-based persistence patterns.

Configure SAP BTP subaccounts, service instances, roles, and development spaces, including connectivity artifacts for external integrations. Package and deploy applications using MTA artifacts.

Integrate LLM-powered features into BTP applications, managing tool calling, orchestration, memory, and safety boundaries. Build retrieval-grounded experiences (RAG) for enterprise content and APIs, with fallback mechanisms.

Establish evaluation loops to monitor and measure AI behavior changes and prevent regressions.

Utilize Git for source control and collaboration, operating within Agile/Scrum methodologies. Debug and resolve issues across backend, database, and service exposure.

Requires a minimum of 3 years of experience in SAP BTP application development.

Essential skills include proficiency in SAP BTP application development fundamentals, covering platform architecture, administration basics, solution design, and frontend/backend build. Demonstrated experience in full-stack implementation patterns, including backend services, APIs, data models, and UI integration is crucial.

Strong software engineering fundamentals, such as clean code principles, a testing mindset, and CI/CD orientation, are expected. The ability to transition seamlessly from prototype to production is a key expectation for AI-native applications.

Additional beneficial skills involve practical exposure to common BTP app development tooling and patterns, familiarity with structured learning paths like BTP Application Development, and an understanding of platform building blocks as referenced in community materials.

This role emphasizes owning AI behavior within the product—orchestration, grounding, evaluation, and safety boundaries—as part of delivery, rather than solely focusing on AI-assisted development or training foundation models from scratch.