AI Engineer responsible for designing, building, and maintaining production AI systems such as Retrieval-Augmented Generation and agentic workflows. The role leverages Python, AWS services, and modern AI frameworks to deliver data-driven solutions and internal tools. Key Responsibilities: • Design and maintain production Retrieval-Augmented Generation systems and agentic AI workflows • Build multi-step agents using LangGraph, LangChain, CrewAI, or equivalent, implementing tool-use and function-calling with human-approval guardrails • Develop front-end interfaces with React, Streamlit, Gradio, or similar technologies • Create REST API integrations and document-processing pipelines that ingest, chunk, embed, and retrieve governed content • Implement vector embeddings, semantic and hybrid retrieval, and model-evaluation practices addressing drift and hallucination • Deliver demonstrable solutions and continuously learn as AI capabilities mature Qualifications: • 3+ years of data and/or AI engineering experience; candidates with ~2 years may be considered if project depth is strong • At least one year of hands-on LLM and RAG implementation experience, including at least one production deployment or significant project that can be demonstrated • Hands-on experience building agentic AI workflows with multi-step orchestration, tool use, function calling, and human-in-the-loop controls • Strong Python development experience and modern software-development foundation • Experience building user-facing applications or internal tools using React, Streamlit, Gradio, or equivalent • Application-level REST API development and integration experience connecting AI back ends to applications • Working knowledge of AWS cloud services used to build or deploy AI applications • Experience with vector embeddings, vector databases or vector search, semantic retrieval, and/or hybrid retrieval patterns • Working knowledge of MLOps and model evaluation, including drift, hallucination, output quality, and production readiness • Strong logical problem-solving ability, curiosity, and a learner-doer mindset Preferred Skills: • Databricks experience, particularly Databricks Vector Search • Amazon Bedrock or comparable managed, multi-model AI service experience • Hands-on experience with LangGraph, LangChain, CrewAI, or equivalent agent framework • SharePoint and Microsoft Graph API integration experience for governed document ingestion • Experience working in a Microsoft-oriented environment, including Copilot-related solutions • Applied machine-learning experience beyond basic generative AI, including model delivery, fine-tuning, or evaluation • SQL, exploratory data analysis, and familiarity with governed healthcare, quality-measure, claims, or regulated datasets • Experience presenting or demonstrating completed technical work to internal users or leadership