Embark on a journey to build AI-native, data-centric products on SAP BTP Datasphere. This role combines expertise in enterprise data warehousing and semantic modeling with cutting-edge agentic AI architectures, including LLMs and integrated tools. The objective is to move beyond traditional dashboards and create intelligent data experiences, such as data agents, conversational analytics, and grounded insights, all built upon governed Datasphere models and connected enterprise sources.

SAP Datasphere serves as a powerful data warehousing solution with extensive integration capabilities, forming the foundation for these innovative solutions. You will be instrumental in shaping the future of data interaction within the organization.

Design and implement governed data products within Datasphere, utilizing concepts like Spaces and shareable models. Develop semantic models optimized for both analytics and AI consumption, ensuring clear entity definitions and lineage-friendly design.

Create grounded AI experiences by linking LLM applications to Datasphere's curated models and enterprise data sources, guaranteeing traceable and reliable AI responses. Engineer sophisticated retrieval strategies that respect domain boundaries, data freshness, and access controls.

Facilitate the transition from legacy warehouse investments by leveraging approaches such as reusing SAP BW models and skills with Datasphere/BW bridge patterns for phased cloud modernization. Implement layered design patterns (e.g., Bronze/Silver/Gold) for data landing, cleansing, and publication, maintaining clear consumption rules.

Build data agents capable of planning, invoking tools, retrieving context, and generating cited answers. Implement prompt templates, tool schemas, and safe action boundaries for robust enterprise-grade usage. Establish evaluation loops for conversational analytics and data agents, and add 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 the development of reusable patterns and accelerators for consistent delivery across various domains.

A minimum of 3 to 5 years of experience is required for this role. A strong foundation in SAP BTP Datasphere is essential, encompassing data modeling, spaces, sharing patterns, and enterprise semantic design. You should possess solid data warehousing fundamentals and the ability to translate complex business domains into governed analytical models.

Hands-on experience with LLMs and RAG is crucial, including proficiency in retrieval, grounding, prompt and tool design, and evaluation techniques. Excellent software engineering fundamentals are expected, with a mindset geared towards testability, CI/CD, and reliable integrations.

Beneficial skills include migration and modernization experience using BW bridge style transition patterns, and implementation of layered architectures (Bronze/Silver/Gold) for scalable analytics delivery. Familiarity with vector search and embedding pipelines for integrating external AI retrieval components would also be advantageous.

This role does not involve training foundation models from scratch; the focus is on building agentic applications and governed retrieval over enterprise data. You will own the AI behavior, including grounding, evaluation, and safety, end-to-end. A 15-year full-time education is a prerequisite for this position.