ESaaS - SAP - Technical - Basis

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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