SAP Gen AI Hub

We are Seeking a forward-thinking professional with an AI-first mindset to to design, build, and operationalize enterprise-grade SAP GenAI solutions & experience with with the SAP Business Technology Platform (BTP) & other AI cloud platforms

The ideal candidate will combine deep expertise in AI Core, Generative AI Hub, Large Language Models (LLMs), and Knowledge Graphs with hands-on experience orchestrating intelligent pipelines using LangChain / LangGraph frameworks, Vector Engines, and Retrieval-Augmented Generation (RAG) architectures.

Roles & Responsibilities:

- Lead AI-driven solution design and delivery using Generative and Agentic AI to solve complex business problems, automate processes, and integrate intelligent insights into enterprise operations for measurable impact.

- Serve as a Subject Matter Expert (SME) for SAP BTP and GenAI solutions.

- Building technical architecture design aligning with SAP and enterprise standards.

- Architect and implement Generative AI pipelines on SAP BTP, leveraging SAP AI Core, Generative AI Hub, and SAP HANA Cloud (Vector Engine + Knowledge Graph Engine).

- Design and manage RAG (Retrieval-Augmented Generation) and GraphRAG workflows to improve the grounding, accuracy, and interpretability of LLM outputs.

- Integrate Large Language Models (LLMs) and Foundation Models (FMs) with enterprise data sources through grounding modules, vector similarity search, and semantic search.

- Build Knowledge Graphs and ontologies to model enterprise domains and link contextual data for reasoning and relationship-aware GenAI applications.

- Develop LangChain / LangGraph-based orchestration pipelines for prompt templating, retrieval, generation, and post-processing.

- Implement data-masking, content filtering, and schema-based output parsing to ensure compliance, privacy, and structured response formats.

- Collaborate with development teams using SAP Cloud Application Programming (CAP) model to embed AI capabilities into cloud-native applications.

- Work with multitenant SaaS architectures ensuring secure tenant isolation and hyperscaler-agnostic deployments.

- Employ chunking, embedding generation, and vector store management to enable efficient information retrieval and contextualization.

- Optimize orchestration pipelines to handle prompt templating, query rewriting, and fusion techniques (e.g., Reciprocal Rank Fusion) for enhanced retrieval precision.

- Lead end-to-end lifecycle of GenAI projectsfrom model integration and fine-tuning in AI Core to deployment, monitoring, and continuous improvement.

- Collaborate and manage cross-functional teams to deliver high-impact solutions on time and within scope.

- Map business requirements to AI-powered solution architectures.

- Mentor and upskill team members through knowledge-sharing sessions and best practice frameworks.

- Ensure solution scalability, performance, and responsible AI usage principles are embedded throughout the development lifecycle.

- Track and report project progress, ensuring strategic alignment with business objectives.

Professional & Technical Skills:

- Deep understanding of SAP BTP services especially AI Core, Generative AI Hub, HANA Cloud (Vector Engine and Knowledge Graph Engine).

- Expertise with Large Language Models, Foundation Models, and LLM Orchestration Frameworks such as LangChain, LangGraph, or Semantic Kernel.

- Hands-on experience designing Retrieval-Augmented Generation (RAG) pipelines with embedding, chunking, and vector similarity search.

- Proficiency in Knowledge Graph design, GraphRAG, and ontology modelling using SAP HANA Cloud or graph databases.

- Strong grasp of data grounding, semantic enrichment, and enterprise contextualization.

- Experience with schema-based output parsing, prompt templating, and prompt-engineering best practices & AI evaluation frameworks.

- Familiarity with content filtering, data masking, and AI governance / compliance frameworks in enterprise environments.

- Working knowledge of CAP (Cloud Application Programming model) and SAP Extension Suite for integrating GenAI into enterprise apps.

- Understanding of vector stores, vector search, and semantic search APIs in HANA Cloud.

- Exposure to multi-tenant SaaS architecture, hyperscaler-agnostic deployments, and MLOps pipelines for AI solutions.

- Have handled deployment of large-scale SAP applications, infrastructure, data, integrations, and related systems.

- Expertise in application design principles, cloud-native development, and integration within SAP ecosystem.

- Familiarity with integration techniques and tools within the SAP ecosystem.

- Strong understanding of application design principles and methodologies.

- Ability to align AI capabilities with business objectives while ensuring scalability, responsible use, and tangible value realization.

- Ability to analyze and optimize application performance.

Technical Experience

- End-to-end Python application development, with hands-on experience on agentic AI frameworks.

- Experience in building SAP BTP GenAI application leveraging SAP AI Core & Gen AI Hub.

- Experience in building APIs and ETL pipelines using Python.

- Exposure to LLM (Large Language Model) integration and LangChain or similar frameworks.

- Familiarity with Agentic AI frameworks such as LangGraph, CrewAI, or equivalent.

- Proven capability in identifying and implementing BTP Business AI Services.