Generative AI Engineer

Level - Manager/Senior Manager Must have skills :

SAP Generative AI

Educational Qualification :

15 years full time education

Summary:

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. You will work with multi-disciplinary teams to embed Generative AI into SAP-centric business applications and processes, ensuring scalability, compliance, and measurable business impact.

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.

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.