SAP Gen AI Hub

Project Role : Custom Software Engineer
Project Role Description : Develop custom software solutions to design code and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable high-performing solutions tailored to specific business needs.
Must have skills : SAP Gen AI Hub
Good to have skills : NA
Minimum 5 year(s) of experience is required
Educational Qualification : 15 years full time education

Summary:
We are seeking an experienced Data Engineer to build and manage the data foundation required for enterprise-scale SAP Business AI solutions. The ideal candidate will be responsible for designing developing and governing AI-ready data platforms that enable advanced analytics Generative AI and intelligent business processes. The role involves identifying and preparing business-critical data sources across SAP and non-SAP systems establishing robust data governance practices and ensuring high-quality secure and trusted data availability for AI consumption. The candidate will work closely with AI Architects AI Engineers business SMEs and functional teams to support the successful delivery of scalable and business-driven AI solutions.
Key Responsibilities
Identify acquire and prepare business-critical data from SAP and non-SAP systems for AI use cases.
Design and build AI-ready datasets to support SAP Business AI and Generative AI initiatives.
Develop and maintain data pipelines integration frameworks and data transformation processes.
Design grounding mechanisms and context retrieval solutions to support GenAI applications.
Establish and enforce data quality lineage metadata and governance standards.
Develop and maintain semantic models knowledge bases and AI-ready data repositories.
Ensure secure compliant and governed access to enterprise data used by AI solutions.
Collaborate with business SMEs and stakeholders to validate data readiness and business relevance.
Optimize data architecture and performance to support AI and analytics workloads.
Support AI solution deployment through data provisioning monitoring and operational support.
Implement data monitoring observability and issue resolution processes.
Contribute to best practices reusable assets and data engineering standards within the AI delivery team.