We are looking for a visionary AI/ML Engineer to lead the development of autonomous AI Agents within our procurement ecosystem. You will be responsible for integrating cutting-edge LLMs and Agentic frameworks with SAP Ariba and SAP BTP to automate sourcing, contract analysis, and supplier negotiations. Your goal is to transform manual procurement tasks into intelligent, self-optimizing workflows.

Key Responsibilities :

- Agentic Framework Development : Design and deploy AI Agents using frameworks like LangGraph, AutoGPT, or CrewAI to handle multi-step procurement tasks (e.g., automated RFQ generation and bid evaluation).

- SAP Ariba Integration : Build seamless connectors between AI models and SAP Ariba APIs to extract data, trigger workflows, and update procurement records.

- RAG Implementation : Develop Retrieval-Augmented Generation (RAG) pipelines to allow AI Agents to "read" and analyze internal SOWs, contracts, and historical TMS data.

- Model Optimization : Fine-tune LLMs for procurement-specific language, ensuring high accuracy in legal and financial terminology.

- Collaboration : Work closely with Soumendra (TMS) and Mrinal (AI for SCM) to ensure AI agents align with broader supply chain logistics and transportation logic.

Technical Qualifications :

- Core AI : Proven experience with Large Language Models (LLMs), Prompt Engineering, and fine-tuning.

- Agentic AI : Hands-on experience building AI Agents that can use tools, browse the web, or interact with APIs autonomously.

- SAP Ecosystem : Deep understanding of SAP Ariba (Source-to-Pay, Contract Management) and SAP BTP (Business Technology Platform).

- Programming : Mastery of Python and frameworks like PyTorch or TensorFlow.

- Data Architecture : Experience with Vector Databases (e.g., Pinecone, Weaviate, or Milvus) for managing procurement knowledge bases.

Preferred Experience :

- Experience in Supply Chain Management (SCM) or Fintech sectors.

- Familiarity with SAP Graph or SAP AI Core for deploying models within the SAP landscape.

- Background in Natural Language Processing (NLP) specifically for legal contract extraction.