Title:- AI Engineer Location: REMOTE - can sit anywhere in US but needs to work EST hours 6 months contract to hire – MUST BE ABLE TO CONVERT w/out Sponsorship Note: only USC or GC required. Position Overview Join our cutting-edge AI initiative to build intelligent agents that seamlessly integrate with our Microsoft Fabric Data Lake as the central data hub, connecting structured data from Infor M3 ERP, Salesforce CRM, Anaplan planning platform, Uncountable PLM, and Freshworks helpdesk alongside unstructured data from SharePoint, file systems, and document repositories. We're seeking an AI Specialist to architect next-generation agents that understand and interact with complex business processes by leveraging our unified data architecture. This role involves creating sophisticated RAG systems, vector databases, and multi-modal AI capabilities that transform how our organization leverages both structured enterprise data and unstructured content across all touchpoints - from manufacturing and supply chain to customer relationships and product lifecycle management. Key Responsibilities: • AI Agent Architecture • System Integration & Data Processing • Multi-Platform AI Development Required Skills • 5-10 years AI/ML development with enterprise data integration • 3+ years Microsoft Fabric, Azure Data Lake, or similar lakehouse platforms • Advanced Python with AI/ML libraries (LangChain, LlamaIndex, Transformers) • SQL/KQL proficiency for complex data querying and analysis • Vector database expertise (FAISS, Pinecone, Weaviate, ChromaDB) • RAG system architecture and implementation at enterprise scale • Multi-LLM integration (OpenAI, Anthropic, Google, Cohere APIs) • Prompt engineering and advanced AI agent orchestration • SharePoint API integration and document processing • RESTful API design and microservices architecture • Real-time data streaming and event-driven systems • Enterprise security and authentication (OAuth, SSO) • Full-stack development (React/Angular frontend, FastAPI/Node.js backend) • Cloud platforms (Azure) • Containerization (Docker, Kubernetes) and DevOps practices • CI/CD pipelines and automated testing frameworks