• Design and maintain ETL pipelines that process and classify unstructured data for Retrieval-Augmented Generation (RAG) systems. • Support the development of agent-based architectures using reasoning and acting patterns such as ReAct. • Build and maintain agent workflows using node-based orchestration frameworks such as LangGraph. • Implement agent memory strategies, including short-term event memory and long-term memory approaches such as summarization, semantic memory, episodic memory, and user preference storage. • Develop system prompts and intent-handling prompts that support reliable agent interactions. • Create evaluation tests and performance benchmarks to measure LLM agent performance. • Build tools that allow LLM agents to interact with external systems and services. • Apply best practices around prompt security, input sanitization, and safe handling of user-generated content.