Job Title: Full Stack Developer

Location: Pune, Delhi (Hybrid, On site)

Company / Department Overview: Tax Technology Transformation is at the forefront of AI innovation, developing cutting-edge solutions that transform Tax function.

We are on the lookout for a Full Stack Engineer with expertise in React, Node.js, and AI technologies to develop a sophisticated Retriever-Augmented Generation (RAG) based chatbot. The ideal candidate will have hands-on experience with vector embeddings, Elastic databases, and frameworks like LangChain.

Key Responsibilities:

Build and maintain the front end of the chatbot application using React, ensuring a seamless user experience. Develop and manage the backend services in Node.js, integrating with AI models and handling server-side logic. Work with vector embeddings to enhance the chatbot's understanding and response accuracy. Implement and maintain databases, particularly Elastic, to manage the chatbot's knowledge base efficiently. Utilize frameworks such as LangChain to streamline the development of language-based AI applications. Collaborate with AI researchers to optimize the RAG model and improve the chatbot's performance. Ensure the application's scalability, security, and data protection. Document the development process, architecture, and best practices.

Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field. 3+ years of experience with strong experience with React and Node.js in a production environment. Proficiency in working with vector embeddings and understanding their role in AI applications. Experience with Elastic or similar databases for storing and querying large datasets. Familiarity with AI frameworks and libraries, particularly those related to NLP and chatbot development. Solid understanding of RESTful API design and development. Knowledge of cloud services and deployment (AWS, Azure, GCP). Proficient in using version control systems like Git. Prior experience building conversational AI or chatbots. Understanding of machine learning operations (MLOps) and deployment of AI models. Experience with containerization and orchestration tools (Docker, Kubernetes). Familiarity with CI/CD pipelines and automated testing frameworks.