ai-engineer
AI Engineer
Purpose
Provides expertise in end-to-end AI system development, from LLM integration to production deployment. Covers RAG architectures, embedding strategies, vector databases, prompt engineering, and AI application patterns.
When to Use
- Building LLM-powered applications or features
- Implementing RAG (Retrieval-Augmented Generation) systems
- Integrating AI APIs (OpenAI, Anthropic, etc.)
- Designing embedding and vector search pipelines
- Building chatbots or conversational AI
- Implementing AI agents with tool use
- Optimizing AI system latency and cost
Quick Start
Invoke this skill when:
- Building LLM-powered applications or features
- Implementing RAG systems with vector databases
- Integrating AI APIs into applications
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