Vector Search & LLM Specialist

As an AI Architect at our company, you will be responsible for designing and implementing cutting-edge generative AI systems with a focus on Retrieval-Augmented Generation (RAG). Your role will involve connecting large language models to our data sources to provide accurate, contextual, and valuable responses. Some of your key responsibilities will include: - Designing and implementing RAG architectures combining large language models with knowledge bases - Optimizing vector search for quick retrieval of relevant information - Managing vector databases and developing indexing strategies - Creating and refining prompts for models like GPT-4 and Claude - Processing and managing large datasets for AI systems - Fine-tuning and customizing models to meet specific needs - Planning system integrations for seamless operation - Benchmarking performance and scalability planning as user base grows To excel in this role, you should be comfortable working with: - Large Language Models from providers like OpenAI and Anthropic - Vector databases such as Pinecone, Weaviate, or PGVector in Postgres - Embedding models and techniques - RAG frameworks like LangChain and LlamaIndex - Vector search libraries including FAISS - Deep learning frameworks like PyTorch or TensorFlow - Distributed computing for handling larger workloads You will love working with us as you will be at the forefront of AI innovation, combining the latest LLMs with knowledge retrieval technologies. Your contributions will directly impact how our AI systems understand and respond to user needs, enhancing their helpfulness, accuracy, and trustworthiness. If you are passionate about pushing the boundaries of RAG models and have 4-6 years of experience in this field, we are excited to discuss this opportunity with you! This is a full-time position based in Bangalore, and the ideal candidate should have at least 4 years of experience as a Vector Search & LLM Specialist.,