Ai Agent Engineer

Key Responsibilities

• Agent Orchestration: Assist in designing and implementing agentic workflows using frameworks like LangChain, CrewAI, or AutoGen. - Tool & Function Integration: Help develop and integrate "tools" (APIs, Python scripts, search engines) that allow LLMs to interact with the real world. - Prompt Engineering & Reasoning: Experiment with advanced prompting techniques (Chain-of-Thought, ReAct, Reflexion) to improve the reasoning capabilities of AI agents. - RAG Pipeline Development: Support the implementation of Retrieval-Augmented Generation (RAG) to give agents access to private, real-time data. - Evaluation & Testing: Develop frameworks to test agent reliability, accuracy, and "hallucination" rates. - Rapid Prototyping: Quickly build "Proof of Concept" (PoC) agents to test new AI capabilities and workflows.