Engineer

As a talented and passionate RAG (Retrieval-Augmented Generation) Engineer with strong Python development skills, your role will involve working on cutting-edge NLP solutions that integrate information retrieval techniques with large language models (LLMs). The ideal candidate will have experience with vector databases, LLM frameworks, and Python-based backend development. **Key Responsibilities:** - Designing and implementing RAG pipelines that combine retrieval mechanisms with language models - Developing efficient and scalable Python code for LLM-based applications - Integrating with vector databases like Pinecone, FAISS, Weaviate, and more - Fine-tuning and evaluating the performance of LLMs using various prompt engineering and retrieval strategies - Collaborating with ML engineers, data scientists, and product teams to deliver high-quality AI-powered features - Optimizing system performance and ensuring the reliability of RAG-based applications **Qualifications Required:** - Strong proficiency in Python and experience in building backend services/APIs - Solid understanding of NLP concepts, information retrieval, and LLMs - Hands-on experience with at least one vector database - Familiarity with Hugging Face Transformers, LangChain, LLM APIs - Experience in prompt engineering, document chunking, and embedding techniques - Good knowledge of working with REST APIs, JSON, and data pipelines Additionally, a Bachelors or Masters degree in Computer Science, Data Science, or a related field is preferred for this position. Experience with cloud platforms like AWS, GCP, or Azure, exposure to tools like Docker, FastAPI, or Flask, and an understanding of data security and privacy in AI applications would be beneficial.,