Job
Description
We are seeking an experienced developer to design and implement a Retrieval-Augmented Generation (RAG) knowledge base that enhances team productivity through smart document organization and conversational access. The ideal candidate will also build a user-friendly AI-powered chatbot , integrated with Slack or a custom interface, enabling seamless access to information. Key Responsibilities: Architect and develop a RAG-based knowledge base to store and manage internal documents and project files. Implement document ingestion, embedding, and retrieval pipelines. Integrate a conversational bot capable of querying the knowledge base using natural language (Slack and/or custom interface). Ensure secure, scalable, and efficient performance across the knowledge system. Design intuitive user experiences for non-technical team members to access information easily. Collaborate with stakeholders to understand content structure and workflow needs. Required Skills: Proven experience with RAG pipelines , vector databases , and embedding models . Hands-on expertise in OpenAI GPT-3/4 , ChatGPT , LangChain , AgentGPT , or similar frameworks. Experience integrating conversational bots with Slack , Microsoft Teams , or web-based UIs. Proficiency in Python , Node.js , or any backend stack suitable for AI/ML workflows. Knowledge of document processing , OCR , text chunking , and metadata tagging . Strong problem-solving, organizational, and communication skills. Preferred Qualifications: Prior experience building internal AI tools for enterprise productivity. Familiarity with knowledge management , document classification , and semantic search . Background in deploying models using AWS , GCP , or Azure . Show more Show less
