will create reusable agent capabilities, orchestration patterns, tool integrations, memory and retrieval services, evaluation frameworks and governance controls that allow teams to adopt agentic automation safely at scale. You will treat agents as production software: versioned, tested, observable, secure, cost-controlled and accountable. Working across Platform Engineering, Architecture, Security … agent or LLM-powered systems, not only experimenting with chat interfaces or prompt prototypes. Strong software engineering capability in Python, including API design, automated testing, asynchronous processing, dependency management and production debugging. Practical experience with agent orchestration, structured tool calling, workflow state, retrieval-augmented generation and human-in-the-loop ...