Hands-On AI Engineering: Recent experience building LLM and agentic systems that ran in production: agent orchestration (LangGraph, CrewAI, AutoGen, Semantic Kernel, OpenAI Agents SDK, or equivalents), Model Context Protocol (MCP) tooling, retrieval and vector stores, and LLMOps discipline-evaluation-first development, prompt and agent versioning, regression testing, observability for non-deterministic outputs, cost attribution. Agent Identity and Security Judgment: A clear position on securing autonomous systems: agents as first-class principals rather than credential-holders impersonating humans, short-lived machine identity, vault-backed scoped secrets, delegation with preserved provenance, default-deny tool access, prompt-injection defense, and audit trails your security team can use.