LLM Engineer

Key Responsibilities:

• Design and deploy end-to-end Generative AI applications tailored for specific business use cases.
• Build and optimize Retrieval-Augmented Generation (RAG) pipelines to combine LLMs with external knowledge sources.
• Integrate vector databases (e.g., ChromaDB, Pinecone, LanceDB) for semantic search, embedding storage, and efficient retrieval of large-scale datasets.
• Fine-tune pre-trained LLMs for domain-specific tasks, ensuring high accuracy and relevance of generated outputs.
• Collaborate with data engineers, ML engineers, and product teams to integrate AI solutions into applications and workflows.
• Conduct testing, evaluation, and monitoring of AI models to ensure performance, fairness, and reliability.
• Research emerging LLM technologies, frameworks, and tools to continuously enhance solution capabilities.