Artificial Intelligence Engineer

Requirements: 4+ years of experience building and supporting production software, data engineering, or AI/ML solutions within enterprise environments Strong hands-on development experience with Python and SQL, including building production-ready applications, data pipelines, APIs, or backend services 1+ year of hands-on experience developing applications utilizing Large Language Models (LLMs), Generative AI, or Agentic AIDemonstrated experience taking at least one LLM-based application from development through production deployment and supporting real-world users Experience designing and building Retrieval-Augmented Generation (RAG) solutions that leverage enterprise data, document repositories, and other governed information sources Strong hands-on experience with Databricks, including Unity Catalog, Delta tables, Databricks Jobs, serverless compute, and working within governed enterprise data environments Experience developing document extraction and processing pipelines that transform large volumes of unstructured documents into structured, searchable, and queryable data Understanding of AI agent architecture and design, including tool selection, permissions, grounding, orchestration, and defining appropriate boundaries for agent behavior Experience implementing AI guardrails and human-in-the-loop workflows to ensure recommendations are reviewed and approved before triggering downstream actions Experience evaluating AI and RAG solutions for accuracy, retrieval quality, latency, reliability, and cost, with the ability to use evaluation results to continuously improve production performance Understanding of AI observability, tracing, monitoring, and auditability within production environments, particularly when working with sensitive or highly governed enterprise data