Data Scientist

Role & responsibilities

motivated Full Stack AI Engineer to design, develop, and deploy AI-powered enterprise applications integrating retrieval-augmented generation (RAG), LLM agents, and scalable web systems. The role involves complete ownership of the development lifecyclefrom frontend to backend, from AI integration to production deployment on Azure Cloud. You will work on a flagship intelligent chatbot platform that connects users to enterprise data through seamless conversational interfaces, leveraging the latest in Generative AI, vector databases, and speech services. Key Responsibilities AI Integration & Architecture - Design and implement RAG-based chatbot architectures combining OpenAI, Azure AI Search, and Weaviate for intelligent information retrieval. - Integrate LLMs and embeddings pipelines to provide context-aware conversational experiences. - Implement speech-to-text (STT) and text-to-speech (TTS) flows using Azure Speech Services for multimodal interactions. - Optimize AI workflows for performance, token efficiency, and compliance. Backend Development (Python & Flask) - Build scalable and secure RESTful APIs with Python Flask. - Design modular service layers for handling AI orchestration, domain data ingestion, and retrieval logic. - Integrate Azure Functions for event-driven automation, background tasks, and asynchronous processing. - Manage data persistence using Azure Cosmos DB and other scalable storage options. - Implement authentication, entitlement checks, and session management for multi-tenant applications. Frontend Development (React + TypeScript) - Develop dynamic, high-performance React TypeScript interfaces for the AI chat platform. - Architect reusable UI components and ensure responsive design across devices. - Integrate frontend workflows with backend APIs and WebSocket streams for real-time updates. - Utilize Redux for global state management and MUI (Material UI) for consistent theming.

Preferred candidate profile