We are seeking a Senior AI Engineer with deep expertise in large language models (LLMs), Retrieval-Augmented Generation (RAG), and vector database optimization . This role is critical in developing scalable AI systems capable of processing and retrieving insights from vast volumes of unstructured data.

Key Responsibilities

• Architect and optimize RAG pipelines for high-performance retrieval across large datasets.
• Implement long-term memory solutions for AI models, ensuring contextual continuity over extended interactions.
• Develop and fine-tune embedding strategies for text, metadata, and structured knowledge representation.
• Work with vector databases (FAISS, Weaviate, Pinecone, ChromaDB) to enable efficient semantic search at scale.
• Design and implement document chunking strategies to enhance retrieval efficiency and AI-generated outputs.
• Fine-tune and integrate LLMs (GPT, DeepSeek, Qwen, Llama, etc) for real-world enterprise applications.
• Collaborate with cross-functional teams to enhance AI-driven workflows with advanced knowledge retrieval capabilities.

Required Qualifications

• Proven expertise in LLM architecture and optimization , particularly in retrieval-based AI systems.
• Extensive experience with vector search technologies and embedding optimization .
• Strong proficiency in Python , along with frameworks such as PyTorch, TensorFlow, LangChain, or similar .
• Deep understanding of document chunking, multi-modal embeddings, and scalable indexing techniques .
• Experience designing scalable AI infrastructure in cloud or hybrid environments.
• Familiarity with enterprise data systems and best practices for AI model deployment.

Preferred Experience

• Experience in multi-turn conversational AI and long-term memory frameworks.
• Track record of building and optimizing large-scale RAG implementations .
• Prior contributions to open-source AI frameworks or published research in the field.

Why Join Us?

This role presents an opportunity to work on cutting-edge AI challenges in a high-impact environment. The selected candidate will play a pivotal role in advancing AI-driven knowledge retrieval, long-term memory, and enterprise AI capabilities.

If you are interested in joining a team driving innovation in AI-powered retrieval systems, we welcome your application.

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