LangChain and Python Developer – Singapore
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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 latency, and adherence to cost constraints.
Evaluation: Develop metrics and evaluation frameworks for testing and monitoring the quality and reliability of LLM outputs.
Required Qualifications
Bachelor's degree in Computer Science, Data Science, or a related field.
3+ years of professional experience in Python development.
1+ years of hands‑on experience developing with LangChain or similar LLM orchestration frameworks.
Experience with vector databases (e.g., Pinecone, Chroma, Milvus) and embedding models.
Solid understanding of cloud platforms (AWS, Azure, or GCP) for application deployment.
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 latency, and adherence to cost constraints.
Evaluation: Develop metrics and evaluation frameworks for testing and monitoring the quality and reliability of LLM outputs.
Required Qualifications
Bachelor's degree in Computer Science, Data Science, or a related field.
3+ years of professional experience in Python development.
1+ years of hands‑on experience developing with LangChain or similar LLM orchestration frameworks.
Experience with vector databases (e.g., Pinecone, Chroma, Milvus) and embedding models.
Solid understanding of cloud platforms (AWS, Azure, or GCP) for application deployment.