AI Engineer Plugin - LLM development, prompt engineering, RAG systems, fine-tuning, and agent frameworks
AI agent development with LangChain, CrewAI, AutoGen, and tool integration patterns.
LLM evaluation frameworks, benchmarks, and quality metrics for production systems.
LLM fine-tuning with LoRA, QLoRA, and instruction tuning for domain adaptation.
LLM architecture, tokenization, transformers, and inference optimization. Use for understanding and working with language models.
LLM deployment strategies including vLLM, TGI, and cloud inference endpoints.
Prompt design, optimization, few-shot learning, and chain of thought techniques for LLM applications.
Retrieval Augmented Generation systems with vector search, document processing, and hybrid retrieval.
Vector database selection, indexing strategies, and semantic search optimization.