Conversational AI Engineer

Location: Chennai

Experience: 7+ Years

Work Mode: Work From Office

We are looking for an experienced Conversational AI Engineer with strong expertise in Python, NLP, NLU, LLMs, and chatbot development to design and build intelligent conversational applications and enterprise-grade virtual assistants.

The ideal candidate should have hands-on experience developing context-aware conversational solutions, integrating LLMs, managing multi-turn conversations, and delivering scalable AI-powered chatbot and voice assistant applications.

Key Responsibilities:

• Design, develop, and deploy intelligent chatbots, virtual assistants, and conversational AI applications.
• Build NLP/NLU solutions for intent recognition, entity extraction, sentiment analysis, and dialogue management.
• Develop LLM-powered conversational applications using OpenAI GPT, Google Gemini, Anthropic Claude, Llama, or similar models.
• Implement multi-turn conversations, contextual memory, session management, and dialogue flows.
• Build and integrate RAG-based conversational applications for context-aware and knowledge-driven responses.
• Develop AI-powered workflows using LangChain, LangGraph, and other conversational AI frameworks.
• Integrate chatbots and virtual assistants with REST APIs, CRM, ERP, and enterprise applications.
• Implement function calling, tool calling, and AI agent capabilities.
• Optimize chatbot performance, response accuracy, latency, scalability, and reliability.
• Implement conversation analytics, monitoring, evaluation, and continuous improvement.
• Ensure responsible AI practices, data privacy, security, and hallucination mitigation.

Mandatory Skills:

• 7+ years of experience in software development / AI engineering.
• Strong hands-on experience in Python programming.
• Proven experience in Conversational AI and Chatbot Development.
• Strong understanding of NLP, NLU, Intent Recognition, Entity Extraction, and Dialogue Management.
• Hands-on experience with LLMs such as GPT, Gemini, Claude, or Llama.
• Experience with frameworks such as Rasa, LangChain, LangGraph, or similar.
• Strong knowledge of Prompt Engineering and Context Management.
• Experience implementing RAG, Embeddings, Vector Databases, and Semantic Search.
• Experience building multi-turn conversational systems and contextual memory.
• Strong experience integrating AI applications with REST APIs and backend systems.
• Experience deploying and maintaining production-grade conversational AI solutions.