Conversational AI is responsible for designing, developing, deploying, and optimizing AI-powered chatbots and voicebots using NLP, Machine Learning, and Large Language Models (LLMs). The role aims to enhance customer and business interactions through intelligent, scalable, and human-like conversational experiences while improving automation, customer engagement, operational efficiency, and service delivery.

KEY DUTIES &

RESPONSIBILITIES OF THE ROLE HOLDER:

- Design, develop, test, and deploy chatbot and voicebot solutions using AI/ML and LLM technologies.
- Build and optimize conversational flows, intent recognition, entity extraction, and dialogue management systems.
- Implement and fine-tune LLM-based applications, prompt engineering strategies, and generative AI solutions.
- Develop Retrieval-Augmented Generation (RAG) and knowledge retrieval capabilities for contextual responses.
- Integrate bots with APIs, CRM platforms, databases, enterprise applications, and backend systems.
- Monitor bot performance, conversation analytics, fallback rates, and customer interactions to drive continuous improvement.
- Conduct testing, debugging, troubleshooting, and version management of AI models and conversational systems.
- Collaborate with Product, Operations, and Engineering teams to translate business requirements into AI solutions.
- Ensure adherence to data privacy, security, compliance, and AI governance standards.
- Support deployment, monitoring, and lifecycle management of AI models in production environments.





MINIMUM REQUIREMENTS OF KNOWLEDGE & SKILLS:

- Solid understanding of Artificial Intelligence, Machine Learning, NLP, NLU, and Conversational AI technologies.
- Hands-on knowledge of Large Language Models (LLMs), Generative AI, Prompt Engineering, and AI model evaluation.
- Experience with semantic search, embeddings, vector databases, and knowledge retrieval systems.
- Proficiency in Python programming and AI/ML development frameworks.
- Knowledge of REST APIs, microservices architecture, and system integration methodologies.
- Experience working with cloud platforms such as Azure, AWS, or GCP.
- Understanding of chatbot and voicebot development frameworks and platforms.
- Familiarity with Speech-to-Text (STT) and Text-to-Speech (TTS) technologies.
- Ability to analyze bot performance metrics and optimize conversational experiences.
- Knowledge of MLOps practices, model monitoring, and deployment processes preferred.

Educational Qualifications:

- Bachelor's Degree in Engineering (Computer Science, Information Technology, Artificial Intelligence, Data Science, or related discipline)
- Overall Experience: 2–3 years.
- Relevant Experience: Minimum 2 years of hands-on experience in chatbot/voicebot development, NLP, AI/ML solutions, and LLM-based applications.

Competency &

Skills Required:

- Chatbot & Voicebot Development
- Python, APIs & Cloud Technologies
- Strong Analytical & Troubleshooting Skills
- Collaboration & Continuous Learning Mindset

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