Roles & Responsibilities :
We are seeking a skilled Conversational AI chatbot Developer to join our HR Digital Assistant team. The ideal candidate will have practical knowledge of web development and at least one year of experience working with Chatbot Development, Generative AI, LLMs RAG models, and REST APIs. The candidate should also be proficient in HTML, CSS, JavaScript, Python etc. and have experience with at least one web development framework (e.g. React, Angular). The candidate should be familiar with version control systems such as Git, and possess strong independent problem-solving and analytical skills. The candidate must have an eye for detail, and the ability to work independently and as part of a team. The ideal candidate should also have an eagerness to learn new technologies, as well as experience in prompt engineering and vector search-based knowledge content development and design.
Develop conversational AI solutions with Cognigy platform using Generative AI LLMs, natural language processing (NLP) and machine learning (ML) techniques.
Work with clients to gather requirements and develop conversational AI chatbot applications that meet their needs.
Design and develop REST APIs to integrate conversational AI chatbot applications with existing HRIT systems.
Work with web development frameworks such as React or Angular to develop front-end interfaces for conversational AI chatbot applications.
Create and manage version control repositories using Git.
Troubleshoot issues and debug code to ensure high-quality, error-free applications during development, testing and maintenance operations.
Collaborate with cross-functional teams, including UX designers and software engineers, to ensure the successful delivery of projects and maintenance operations.
Develop and maintain conversational AI chatbot knowledge content and responses.
Knowledge data architecture, technical extraction from internal HR Knowledge base systems, and then perform post process/enrichment/transformation of the knowledge content using programming to fit to vector search-based knowledge stores (RAG model) for accurate answer generation via LLMs.
Design and implement conversation flows and user experiences.
Implement prompt engineering methodologies and techniques to improve AI/NLP scoring and accuracy.
As part of maintenance and support, analyze conversational data to improve the accuracy and effectiveness of conversational AI chatbot applications.
Stay up to date with the latest developments in conversational AI and related technologies.