22 Aug
|
Fittbot
|
Bengaluru
AI Native Data Product Engineering (on Datasphere)
- Design and implement governed data products using Datasphere concepts such as Spaces and shareable models/views, enabling teams to explore, transform, and share curated datasets across domains.
- Build semantic models that are fit for both analytics and AI consumption (transparent entity definitions, measures, hierarchies, lineage-friendly design).
2) Retrieval + Grounding (RAG) over Enterprise Data
- Create grounded AI experiences by connecting LLM applications to Datasphere s curated models and enterprise sources (SAP and non SAP), ensuring responses are traceable to governed data.
- Engineer retrieval strategies that respect domain boundaries (spaces), freshness needs, and access controls, so AI outputs remain reliable and compliant.
3) Hybrid Modernization & Migration (BW bridge patterns)
- Enable transition paths from legacy warehouse investments by leveraging approaches such as reusing SAP BW models and skills with Datasphere / BW bridge, supporting phased cloud modernization.
4)
Lakehouse style Layering & Data Quality by Design
- Implement layered design patterns (e.g., Bronze/Silver/Gold) to land raw data, cleanse/validate, and publish analytics ready modelswhile maintaining clear rules for what s exposed for consumption.
- Embed quality controls, validation checks, and reproducible transformations as part of the delivery lifecycle.
5) Agentic Orchestration & Tooling
- Build data agents that can plan, call tools (query/metadata/lineage), retrieve context, and generate answers with citations—backed by deterministic checks and fallback behaviors.
- Implement prompt templates, tool schemas, and safe action boundaries for enterprise-grade usage.
6) Evaluation, Observability & Responsible AI
- Establish offline/online evaluation loops (golden questions, regression suites, behavior tests) for conversational analytics and data agents.
- Add telemetry for AI interactions (latency, grounding rate, failure modes) to
📌 SAP BTP Datasphere (Bengaluru)
🏢 Fittbot
📍 Bengaluru