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About the Role
A LangChain and Python Developer specializes in building applications leveraging Large Language Models (LLMs) and the LangChain framework. This role focuses on developing, optimizing, and deploying sophisticated RAG (Retrieval-Augmented Generation) systems and generative AI applications.
Key Responsibilities
LLM Application Development: Design and implement end-to-end applications using Python and the LangChain framework to orchestrate complex LLM calls, agents, chains, and custom tools.
RAG System Engineering: Develop and optimize data pipelines for ingestion, chunking, embedding generation, and vector database indexing to improve RAG performance and context relevance.
Model Tuning: Work with various LLMs (e.g., OpenAI, Claude, Llama) and implement prompt engineering techniques and fine-tuning strategies to achieve desired application behavior.
Deployment and Scalability: Deploy and maintain LLM applications in a production environment, ensuring high performance, low la...
Key Responsibilities
LLM Application Development: Design and implement end-to-end applications using Python and the LangChain framework to orchestrate complex LLM calls, agents, chains, and custom tools.
RAG System Engineering: Develop and optimize data pipelines for ingestion, chunking, embedding generation, and vector database indexing to improve RAG performance and context relevance.
Model Tuning: Work with various LLMs (e.g., OpenAI, Claude, Llama) and implement prompt engineering techniques and fine-tuning strategies to achieve desired application behavior.
Deployment and Scalability: Deploy and maintain LLM applications in a production environment, ensuring high performance, low la...
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