services that underpin enterprise AI ecosystems. Guide teams on software architecture, performance, scalability, security, and maintainability. AI governance & LLMOps Architect governance frameworks for auditability, observability, explainability, and compliance. Design guardrails for hallucination, prompt injection, toxicity, and model safety. Establish LLMOps: evaluation pipelines, automated testing, CI/CD, monitoring, and production … with one of Azure, OpenAI, AWS Bedrock, Claude; Kubernetes and cloud-native deployment. LLMOps & evaluation : CI/CD for AI, automated evals, experiment tracking, observability, model lifecycle management. Responsible AI : governance frameworks, guardrails, model safety, compliance, and auditability. Preferred but not required Orchestration frameworks : LangChain/LangGraph, LlamaIndex, CrewAI, AutoGen ...