Acceptance Testing, Access Control, Amazon Web Services (AWS), Application Programming Interface (API), Artificial Intelligence (AI), Automation, Business Processes, Calendar Management, Cloud Architecture, Conversation Engine, Data Management, Data Modeling, Decision Support, Demand Forecasting/Planning, Design Document, ERP (Enterprise Resource Planning), Forecasting, Internet of Things, Knowledge Base, Knowledge Transfer, Management Reporting, Manufacturing, Manufacturing Analysis, Manufacturing Cost, Manufacturing Operations, Manufacturing Software, Manufacturing/Industrial Processes, Materials Management, Microservices, Microsoft Windows Azure, Model Validation, Operational Audit, Plant Management, Product Demonstration, Production Planning, Proof of Concept, Python Programming/Scripting Language, Quality Control, Regulatory Compliance, Reporting Dashboards, SAP, SAP ECC (fka SAP R/3 and SAP ERP), SAP MM, SAP NetWeaver Business Warehouse, Sales, Snowflake Schema, Structured Data, Supply Chain Operations, Use Cases, Variance Analysis
Key Responsibilities:
AI Strategy & Solution Design
Lead end-to-end design and delivery of AI/ML solutions for manufacturing and ERP-integrated use cases including predictive maintenance, demand forecasting, quality control, and process automation.
Architect and implement Generative AI solutions leveraging LLMs for intelligent document processing, chatbots, anomaly detection, and decision-support systems within ERP environments.
Define AI use case roadmaps aligned to manufacturing business processes such as production planning (PP), materials management (MM), plant maintenance (PM), and sales & distribution (SD).
Develop and validate ML models for structured data from ERP systems including SAP S/4HANA, ECC,leveraging Python-based frameworks (scikit-learn, TensorFlow, PyTorch, XGBoost).
Integrate AI/ML outputs back into ERP workflows, dashboards, and reporting layers for real-time business impact.
AI Platform Architecture & ERP Integration
Design scalable AI/ML architectures on cloud platforms (Azure, AWS) with connectors to SAP ECC SAP S/4HANA,
and Snowflake for end-to-end data pipelines feeding AI models.
Build and maintain feature engineering pipelines ingesting manufacturing
data (IoT sensors, MES, SAP transactional data) for real-time and batch AI inference.
Configure Retrieval-Augmented Generation (RAG) architectures, vector stores,
and LLM API integrations to enable intelligent Q&A over enterprise ERP and manufacturing knowledge bases.
Develop and maintain MLOps pipelines using tools such as MLflow, Azure ML,
or SageMaker for model versioning, drift monitoring, and automated retraining.
AI Use Case Implementation & Delivery
Lead end-to-end implementation of Predictive Maintenance, Cost Planning, Manufacturing Analytics, Production Planning AI, and Rolling Forecast processes within SAC.
Configure driver-based planning models, allocation rules, distribution & spreading logic, and advanced formula-based calculations.
Set up Planning Calendars, workflows, task assignments, and review/approval cycles (Schedule phase).
Enable Predict capabilities: configure automated time-series forecasting (predictive scenarios) and planning propositions using SAC built-in ML features.
Support ACT vs. BUD variance analysis, asymmetric reporting, and management reporting dashboards.
Development & Technical Implementation
Develop AI-powered APIs and microservices using Python (FastAPI/Flask) and LangChain / RAG to expose ML model inference endpoints to ERP and manufacturing applications.
Build Python-based ETL and feature engineering pipelines to transform raw SAP/ERP transactional data into AI-ready datasets stored in Snowflake or cloud data lakes.
Create LangChain or similar G enAI orchestration workflows integrating LLMs with structured ERP data to power intelligent assistants and automated reporting tools.
Perform data modeling and semantic layer design in SAP BW/4HANA or Snowflake to support AI feature stores and analytical use cases for manufacturing operations.
Manage model governance, AI ethics guidelines, data access controls, and compliance requirements for AI deployments in regulated manufacturing environments.
Collaboration & Stakeholder Management
Partner with Manufacturing, Operations, Supply Chain, and IT stakeholders to gather AI use case requirements, run discovery workshops, and translate business needs into scalable AI solutions.
Conduct model validation, UAT, end-user training, and knowledge transfer to plant managers, operations analysts, and SAP functional teams.
Collaborate with SAP functional consultants (FI/CO, MM, PP, SD) and data engineering teams on AI integration governance and model deployment cycles.
Prepare and present AI solution design documents, proof-of-concept demos, and business value assessments to senior stakeholders