Responsibilities & Key Deliverables

Key Responsibilities
AI & ML Strategy for Strategic Sourcing Partner closely with Purchasing, Commodity Teams, Supplier Quality, Cost Engineering, and Strategic Sourcing stakeholders to identify AI/ML use cases and business transformation opportunities. Understand and map procurement processes including: RFQ management Supplier evaluation Spend analytics Cost optimization Contract analytics Demand forecasting Supplier risk monitoring Procurement operations automation Define AI roadmap aligned with organizational digital transformation goals. Build scalable AI frameworks and reusable AI components for sourcing functions. AI/ML Solution Development Design, develop, and deploy AI/ML applications for procurement and sourcing functions. Develop predictive, prescriptive, and generative AI solutions using structured and unstructured enterprise data. Build intelligent copilots and AI assistants for procurement users using LLM technologies. Implement: NLP models Recommendation systems Forecasting models Supplier intelligence engines Semantic search systems Document intelligence solutions Generative AI workflows Create AI-enabled dashboards and analytical insights platforms. Large Language Model (LLM) & GenAI Responsibilities Architect and implement enterprise-grade LLM applications. Fine-tune and optimize LLMs for procurement-specific use cases. Build Retrieval-Augmented Generation (RAG) frameworks using enterprise data sources. Integrate AI copilots with sourcing workflows and enterprise systems. Develop prompt engineering frameworks and AI governance standards. Evaluate open-source and commercial GenAI ecosystems for enterprise adoption. Ensure responsible AI, security, compliance, and data governance. --
- Enterprise Systems Integration Lead integration of AI applications with enterprise platforms including:



SAP S/4HANA Qlik SaaS 3DEXPERIENCE (3DX) PLM systems Supplier portals Internal analytics platforms Develop API-based architectures and middleware integrations. Collaborate with IT, Digital, Data Engineering, and Cloud teams for enterprise deployment. Ensure scalability, cybersecurity, reliability, and performance optimization. --
- Full Stack & Application Development Lead development of AI-powered web applications and user interfaces. Build scalable front-end solutions using React. Develop backend AI services and APIs using Python. Implement cloud-native and microservices-based architectures. Drive DevOps and MLOps best practices for continuous deployment and monitoring. --
- Stakeholder & Team Management Work cross-functionally with sourcing leaders, business users, digital teams, and external partners. Conduct workshops to identify automation and AI opportunities. Mentor data scientists, AI engineers, and analysts. Drive vendor evaluations and technology partnerships. Preferred Industries Automobile Farm Sector Education Qualification Bachelor’s or Master’s degree in: Computer Science, Artificial Intelligence, Data Science, Information Technology, Electronics Engineering or related field Preferred:MBA or specialization in Supply Chain / Analytics / AI General Experience 8–15 years of experience in AI/ML, analytics, or enterprise digital transformation. Strong experience in manufacturing, automotive, procurement, or supply chain environments preferred.



Proven track record of delivering enterprise AI applications. Critical Experience Technical Skills Core AI & ML Expert in Python programming Strong expertise in: Machine Learning Deep Learning NLP Generative AI LLM architectures Hands-on experience with: LangChain Vector databases RAG pipelines Prompt engineering AI orchestration frameworks Experience with ML frameworks: TensorFlow PyTorch Scikit-learn --
- Enterprise Systems Strong knowledge of: SAP S/4HANA Qlik SaaS 3DEXPERIENCE (3DX) Enterprise data lakes API integrations Middleware systems --
- Development Skills Strong React development knowledge REST API and microservices architecture expertise Experience with: FastAPI / Flask Docker Kubernetes CI/CD pipelines MLOps platforms Cloud platforms (Azure/AWS/GCP) --
- Data & Analytics SQL and enterprise data modeling expertise Experience handling large-scale enterprise datasets Dashboarding and analytical platform integration experience --
- Preferred Industry Knowledge Automotive purchasing and sourcing processes BOM and cost structure understanding Supplier ecosystem management Manufacturing digital transformation Procurement analytics and spend management --
- Behavioral Competencies Strong problem-solving and analytical mindset Excellent stakeholder management Strong communication and presentation skills Ability to convert business problems into AI-driven solutions Innovation-oriented with execution focus Ability to work in rapid-paced cross-functional environments System Generated Core Skills Analytical Thinking Communication Skills Influencing Skills Project Planning & Execution Risk Analysis Supplier Selection Pricing Price Optimization Supplier Risk Management Sourcing Strategic Sourcing Benchmarking System Generated Secondary Skills Negotiation Project Management Supplier Management

📌 Digitization & Analytics Manager - Digitization & Analytics Manager - Strategic Sourcing (Mumbai)
🏢 Mahindra and Mahindra
📍 Mumbai