Key Responsibilities:

1. AI Solution Development

• • Build and deploy AI/ML models for SAP use cases such as performance forecasting, automation, and intelligent recommendations.
  • Leverage SAP Joule for conversational AI and intelligent assistance.
  • Implement Generative AI solutions (e.g., SAP Copilot, document processing, RAG-based knowledge retrieval) integrated with SAP data sources.

1. Integration with SAP

• • Integrate AI services to SAP BTP, SAP S/4HANA, and SAP Datasphere for conversational AI experiences.
  • Collaborate within & across the teams to identify and prioritize AI use cases.

1. Data Engineering & MLOps

• • Prepare and optimize data pipelines from SAP HANA/CDS views for AI model training and inference.
  • Implement MLOps practices: CI/CD pipelines, model monitoring, retraining workflows, and version control.
  • Configure and extend SAP Joule to deliver personalized, context-aware assistance across SAP applications.

1. Compliance & Governance

• • Ensure adherence to data privacy, security, and Responsible AI principles.
  • Document AI models, prompts, and workflows for auditability and governance.

WHAT YOU BRING:

• 5 - 9 years experience in AI/ML development and SAP technical operations.
• Strong experience in Python, ML frameworks (TensorFlow, PyTorch), and LLM toolchains (LangChain, Hugging Face).
• Hands-on with SAP technologies: S/4HANA, SAP BTP.
• Experience with cloud AI services (Azure AI, AWS SageMaker).
• Experience with MLOps tools (MLflow, Kubeflow) and containerization (Docker, Kubernetes).
• Ensure scalability, robustness, and efficiency of AI applications across various platforms. 
• Analyze project requirements and translate them into AI solution frameworks. 
• Mentor and guide junior AI specialists and team members in best practices and advanced techniques. 
• Stay updated on the latest AI and machine learning trends and integrate relevant technologies and methodologies. 
• Evaluate, select, and deploy AI tools and technologies to leverage our infrastructure capabilities.
• Monitor and assess AI performance metrics, providing insights and recommendations for enhancement. 
• Engage in peer reviews, documentation processes, and develop guidelines for AI strategy implementations.