Key Responsibilities
1. Data Ingestion & Transformation
- Design pipelines to:
- Ingest Excel files from shared folders (SharePoint/Network/Azure storage)
- Convert structured/unstructured data into RAG-ready vector datasets
- Implement data preprocessing, normalization, and metadata tagging
2. SAP Integration & Data Extraction
- Develop integrations with SAP S/4HANA Public Cloud APIs
- Extract transactional and master data for reconciliation/comparison
- Handle authentication, API throttling, and data consistency
3. RAG-Based AI Solution Development
- Build and deploy RAG pipelines using Azure AI services
- Enable:
- Semantic search
- Context-aware data retrieval
- Knowledge grounding from Excel + SAP data
- Maintain vector databases (e.g., Azure AI Search / embeddings store)
4. AI Agent-Based Data Validation
- Design AI agents to:
- Compare SAP vs Excel data
- Identify mismatches, missing records, inconsistencies
- Automate reasoning workflows for:
- Data validation
- Exception identification
- Auto-suggestions for missing data
5. Integration Failure Analysis (SAP CPI)
- Parse and analyse SAP CPI logs
- Correlate failed integration records with:
- Missing/incorrect data
- Mapping errors
- API failures
- Build AI-assisted root cause classification engine
6. Azure-Based Application Development
- Develop and deploy applications on Microsoft Azure
- Use:
- Azure Functions / App Services
- Azure AI / OpenAI services
- Azure Data Factory / Logic Apps
- Ensure scalability, security, and monitoring
7. Automation & Reporting
- Create automated dashboards:
- Failed records summary
- Root cause insights
- Data reconciliation status
- Integrate with Power BI (optional but preferred)
Required Skills & Experience
Technical Skills
- Strong experience in:
- Python / AI development
- RAG architectures & LLM integration
- Hands-on with:
- Azure AI services / Azure OpenAI
- Vector databases (Azure AI Search / FAISS / etc.)
- SAP expertise:
- SAP S/4HANA Public Cloud APIs
- SAP CPI (Cloud Platform Integration)
- Data handling:
- Excel processing, ETL pipelines
- API integration & JSON/XML handling
Preferred Skills
- Experience with:
- AI Agents / Autonomous workflows
- LangChain / Semantic Kernel / similar frameworks
- Data quality and reconciliation solutions
- Knowledge of:
- SAP Datasphere / BTP ecosystem
- Exposure to enterprise integration patterns
Soft Skills
- Strong analytical & problem-solving skills
- Ability to translate business requirements into AI solutions
- Collaboration with SAP, Integration, and Data teams
Experience Level
- 5–10 years (with at least 2–3 years in AI/ML or advanced automation)
Deliverables
- End-to-end AI solution for:
- Data ingestion → RAG conversion → SAP extraction → AI comparison → CPI failure analysis
- Production-ready deployment on Azure
- Automated reporting & monitoring framework
Nice-to-Have Enhancements (Optional Scope)
- Self-healing integration recommendations
- Chatbot interface for querying reconciliation issues
- Predictive failure detection using historical CPI logs
Suggested Role Tag (for hiring portals)
“AI + SAP Integration Engineer | RAG | Azure | CPI”
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