Description

Key Responsibilities

• Design and architect GenAI solutions across SAP and non-SAP enterprise systems
• Build hands on prototypes proof of concepts demos and reusable technical accelerators
• Define reference architectures for SAP GenAI solutions leveraging SAP Business AI, Joule, SAP BTP, SAP Business Data Cloud, SAP Datasphere, S/4HANA, SuccessFactors, Ariba, IBP, MDG, and SAP Integration Services.
• Extend GenAI capability beyond SAP by integrating with hyper-scaler AI platforms enterprise data platforms APIs workflow tools document intelligence vector databases and automation platforms
• Evaluate when to use SAP-native AI hyper-scaler AI opensource models partner platforms or custom-built GenAI solutions
• Design secure scalable compliant and reusable AI architecture patterns for enterprise clients
• Lead technical discovery with client architects CIO teams data teams security teams and SAP program teams
• Convert business use cases into technical solution designs architecture diagrams integration flows estimation models and implementation plans
• Guide engineering teams on prompt design RAG architecture agentic workflows model orchestration API integration data grounding observability and AI governance
• Create technical playbooks reusable components code samples accelerators and implementation standards for the SAP Practice
• Support delivery teams in industrializing GenAI pilots into production grade solutions
• Stay current with SAP Business AI Joule Joule Agents SAP BTP SAP Business Data Cloud hyper-scaler AI services LLM frameworks agent frameworks and enterprise AI trends
• Enable and mentor SAP consultants architects and developers to build deeper GenAI technical capability

Required Experience

• 12 years of experience in SAP architecture enterprise architecture integration architecture cloud architecture or application engineering
• Strong hands-on experience in GenAI solution design and implementation
• Practical knowledge of LLMs, Retrieval-Augmented Generation (RAG), embeddings, vector databases, prompt engineering, agentic AI, model orchestration, API-based integration, and enterprise AI application patterns.
• Experience working with SAP landscapes, including S/4HANA, ECC, SAP BTP, SAP Integration Suite, SAP Fiori, SAP Datasphere, SAP Analytics Cloud, SuccessFactors, Ariba, IBP, MDG, or SAP BW.
• Experience with at least one major cloud and AI ecosystem, such as Microsoft Azure and Azure OpenAI, AWS Bedrock, Google Vertex AI, Databricks, Snowflake, or similar platforms.
• Ability to create working prototypes using modern engineering tools and frameworks
• Strong understanding of enterprise integration APIs event-driven architecture identity and access management security data privacy and compliance
• Ability to work with both SAP functional teams and modern AI cloud engineering teams
• Strong communication skills with the ability to explain technical choices to business and technology stakeholders

Preferred Skills

• Experience with SAP Business AI, Joule, Joule Agents, SAP AI Core, SAP AI Launchpad, SAP Build, SAP CAP, SAP BTP, SAP Business Data Cloud, or SAP Datasphere.
• Hands-on exposure to Python, JavaScript, TypeScript, Node.js, Java, ABAP, CAP, REST APIs, OData, GraphQL, or cloud-native development.
• Experience with LangChain, LlamaIndex, Semantic Kernel, CrewAI, AutoGen, or other AI orchestration frameworks.
• Experience building RAG solutions using enterprise documents, SAP data, business process data, knowledge bases, and structured and unstructured data sources.
• Understanding of SAP clean-core principles and side-by-side extensibility.
• Experience with DevOps, MLOps, LLMOps, CI/CD, observability, testing, and production support for AI solutions.
• Exposure to process mining, workflow automation, document intelligence, test automation, and AI-led application management services (AMS) use cases.
• Ability to create demos and technical assets for client workshops proposals and innovation sessions

Key Skills

Education

Bachelor's degree