Expertise in multi-agent orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen).
Deep knowledge of LLM architectures, RAG implementation, and techniques for fine-tuning models.
Extensive experience with cloud platforms (AWS, Azure, or GCP) and related AI services.
Strong background in data engineering, including building ETL pipelines and managing vector stores.
Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow).
Hands-on experience with MLOps practices and tools (e.g., Docker, Kubernetes, MLflow).
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