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.
