AI Engineer

Infor is seeking an AI Engineer to design and deliver agentic AI solutions using Retrieval-Augmented Generation (RAG), enterprise copilots, intelligent automation, semantic search, and large language models. The role focuses on building intelligent workflows that transform structured and unstructured data into actionable insights. The engineer will develop end-to-end AI pipelines, integrate LLM APIs and agent frameworks, and build scalable AI solutions for enterprise applications. Key Responsibilities: - Implement Retrieval-Augmented Generation (RAG) pipelines for document and knowledge retrieval. - Design and deploy AI agents and enterprise copilots. - Build end-to-end AI data pipelines covering ingestion, embeddings, vector search, inference, and result persistence. - Develop semantic search and intelligent retrieval solutions. - Build natural-language interfaces for analytics and decision intelligence. - Integrate LLM APIs and frameworks such as LangChain and LlamaIndex. - Collaborate with cross-functional teams to translate business requirements into AI solutions. - Ensure scalability, reliability, and performance of AI systems in production.

Required Skills: - Strong experience with SQL and data engineering. - Strong programming skills in Python. - Experience with LLM APIs and prompt engineering. - Hands-on experience with embeddings and vector databases. - Understanding and practical experience with Retrieval-Augmented Generation (RAG). - Knowledge of agentic AI architectures, copilots, chatbot frameworks, and MCP. - Experience with AWS, Azure, or GCP cloud platforms. - Experience with Git, CI/CD pipelines, and REST APIs. - Strong understanding of AI and intelligent automation workflows. - Strong communication and stakeholder management skills. - Familiarity with Agile methodologies. Preferred Skills: - Experience building AI copilots, enterprise chatbots, or agentic AI systems. - Knowledge of LangChain, LlamaIndex, and MLflow. - Understanding of AI model evaluation and continuous improvement techniques. - Experience developing production-ready AI systems.