Conversational AI Developer

Job DescriptionJob Description Job Title: Conversational AI Developer Job Summary We are seeking a Conversational AI Developer to design, develop, and deploy intelligent conversational applications, including chatbots, virtual assistants, and voice-enabled solutions. The ideal candidate will have experience in Natural Language Processing (NLP), Large Language Models (LLMs), dialog management, prompt engineering, and conversational design. You will collaborate with AI Engineers, NLP Engineers, UX Designers, Product Managers, and Software Engineers to deliver engaging, scalable, and production-ready conversational experiences across web, mobile, and voice channels. Key Responsibilities Design, develop, and maintain conversational AI applications for chat and voice interactions. Build dialogue flows, conversation logic, and multi-turn interactions for virtual assistants and chatbots. Develop and integrate solutions using LLMs, NLP models, and Generative AI technologies. Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge sources. Create and optimize prompts, system instructions, and orchestration workflows to improve response quality and user experience. Integrate conversational AI solutions with enterprise applications, APIs, databases, and third-party services. Build RESTful APIs and microservices to support chatbot functionality and backend integrations. Evaluate and improve chatbot performance using conversation analytics, user feedback, and AI evaluation metrics. Implement guardrails, content moderation, authentication, and security best practices for conversational AI applications. Collaborate with UX designers to improve conversation design, user engagement, and accessibility. Deploy, monitor, and maintain conversational AI applications using cloud and MLOps practices. Troubleshoot production issues and continuously optimize model performance and user satisfaction. Required Qualifications Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field. 3 years of experience in conversational AI, chatbot development, NLP, or AI application development. Strong programming skills in Python; experience with JavaScript or TypeScript is a plus. Experience with NLP concepts such as intent recognition, entity extraction, text classification, and dialogue management. Experience working with Large Language Models (LLMs) and prompt engineering. Hands-on experience with AI orchestration frameworks such as LangChain, LangGraph, LlamaIndex, or similar technologies. Experience building RESTful APIs using FastAPI, Flask, or similar frameworks. Familiarity with relational and NoSQL databases. Experience with Git, Docker, and cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform. Preferred Qualifications Experience with conversational AI platforms such as Microsoft Copilot Studio, Azure AI Foundry, Google Dialogflow CX, Amazon Lex, IBM watsonx Assistant, or Kore.ai. Experience implementing Retrieval-Augmented Generation (RAG) using vector databases such as Pinecone, Milvus, Weaviate, Chroma, or Azure AI Search. Familiarity with model serving, API gateways, and AI deployment practices. Experience integrating speech recognition (ASR) and text-to-speech (TTS) technologies for voice assistants. Knowledge of AI agent frameworks, function calling, tool integration, and workflow orchestration. Experience implementing AI safety, governance, evaluation, and observability practices. Familiarity with CI/CD, Kubernetes, and MLOps concepts. Technical Skills Python JavaScript / TypeScript (preferred) FastAPI Flask REST APIs LangChain LangGraph LlamaIndex OpenAI-compatible APIs and LLM integration Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases (Pinecone, Milvus, Weaviate, Chroma) SQL MongoDB Redis Git Docker Kubernetes (preferred) AWS / Azure / Google Cloud Platform Soft Skills Strong problem-solving and analytical skills Excellent communication and collaboration abilities User-centric mindset with attention to conversational experience Creativity in designing natural and effective interactions Ability to work in Agile, cross-functional teams Continuous learning and adaptability Nice to Have Experience developing AI agents with multi-step reasoning and tool integration Experience with multilingual conversational AI applications Knowledge of AI evaluation frameworks, prompt testing, and conversation analytics Familiarity with DevOps, MLOps, and observability tools Cloud, AI, or conversational platform certifications Key Performance Indicators (KPIs) Conversation success and task completion rate User satisfaction (CSAT) and engagement metrics Response accuracy and relevance Average response latency Prompt and workflow optimization effectiveness Reduction in escalation to human agents System availability and reliability Production incident resolution time Location Hybrid / Remote / On-site (as applicable) Employment Type Full-time