product owners, clients, or operational users to understand real workflows, constraints, data quality issues, and adoption barriers, then translate these into working technical solutions. LLM and agent engineering: Build and tune LLM workflows, prompt strategies, schema-driven extraction, tool-calling patterns, agent orchestration, evaluation loops, and human-in-the-loop … agents, tool orchestration, reasoning workflows, Model Context Protocol (MCP), and enterprise-scale automation use cases. Hands-on experience building AI-enabled systems, such as LLM pipelines, document extraction, structured output generation, AI-assisted analytics, prediction interfaces, or agentic workflows. Experience working with business-critical systems where reliability, maintainability, operational support ...