This role involves developing custom software solutions, focusing on building AI-native, data-centric products on SAP BTP Datasphere. The emphasis is on creating intelligent data experiences such as data agents and conversational analytics, leveraging strong enterprise data warehousing and semantic modeling expertise with agentic AI architectures.

The primary goal is to move beyond traditional dashboards into sophisticated, governed data solutions. This includes building semantic models for both analytics and AI consumption, enabling teams to explore and share curated datasets across domains. The position requires a blend of data warehousing, AI development, and software engineering best practices to deliver scalable and high-performing applications.

Design and implement governed data products using SAP BTP Datasphere features like Spaces and shareable models. Build semantic models for AI and analytics consumption, ensuring clear entity definitions and lineage-friendly design.

Create grounded AI experiences by connecting LLM applications to Datasphere models and enterprise sources, ensuring traceability to governed data. Develop retrieval strategies that respect domain boundaries, freshness needs, and access controls for reliable AI outputs.

Implement hybrid modernization strategies using BW bridge patterns for phased cloud migration. Design layered architectures (e.g., Bronze/Silver/Gold) for data landing, cleansing, and analytics publishing while embedding quality controls.

Build data agents capable of planning, tool utilization, context retrieval, and answer generation with citations. Implement prompt templates, tool schemas, and safe action boundaries for enterprise-grade usage.

Establish evaluation loops for conversational analytics and data agents. Implement telemetry for AI interactions to enhance reliability and cost efficiency.

Collaborate closely with business, data governance, and platform teams to align data products with operational workflows. Drive reusable patterns and accelerators for efficient delivery.

A minimum of 2-5 years of experience is required, with at least 3 years in Packaged Application Development.

Essential skills include proficiency in SAP BTP Datasphere for data modeling, spaces, sharing patterns, and enterprise semantic design. Strong data warehousing fundamentals are crucial for translating business domains into governed analytical models.

Hands-on experience with Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), including retrieval, grounding, prompt and tool design, and evaluation is mandatory. Solid software engineering fundamentals, including testability, a CI/CD mindset, and reliable integrations, are also required.

Additional beneficial skills encompass migration/modernization experience with BW bridge style transition patterns, layered architecture implementation (Bronze/Silver/Gold), and familiarity with vector search/embedding pipelines. A 15-year full-time education is a prerequisite for this role.