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”
Responsibilities
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”
Qualifications
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”
Company
At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.
Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.
We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.
We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.