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

The ideal candidate will possess deep expertise in AI Core, Generative AI Hub, Large Language Models (LLMs), and Knowledge Graphs. Hands-on experience orchestrating intelligent pipelines using LangChain/LangGraph frameworks, Vector Engines, and Retrieval-Augmented Generation (RAG) architectures is essential. You will collaborate with multi-disciplinary teams to integrate Generative AI into SAP-centric business applications and processes, ensuring scalability, compliance, and measurable business impact.

- 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. - Serve as a Subject Matter Expert (SME) for SAP BTP and GenAI solutions, building technical architecture designs aligned 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 and GraphRAG workflows to improve the grounding, accuracy, and interpretability of LLM outputs. - Integrate LLMs and Foundation Models 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 for efficient information retrieval and contextualization. - Optimize orchestration pipelines to handle prompt templating, query rewriting, and fusion techniques for enhanced retrieval precision. - Lead end-to-end lifecycle of GenAI projects—from 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.

- Deep understanding of SAP BTP services, especially AI Core, Generative AI Hub, and HANA Cloud (Vector Engine and Knowledge Graph Engine). - Expertise with Large Language Models, Foundation Models, and LLM Orchestration Frameworks like 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. - Experience in deploying large-scale SAP applications, infrastructure, data, integrations, and related systems. - Expertise in application design principles, cloud-native development, and integration 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. - Minimum 3 years of experience required. Completed minimum of 15 years of full-time education with Bachelor's or Master's in Computer Science, IT, or Electronics & Communication from a recognized institution.