IN Business Analyst - AI
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Summary
Business analyst on Fintech Farm's Conversational AI team, designing, building, and optimizing AI-powered chatbots and voicebots using NLP, LLMs, prompt engineering, and RAG. Day to day involves Python development, integrating bots with APIs/CRMs/cloud platforms (Azure, AWS, GCP), and monitoring performance to improve automation and customer engagement.
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:
• Strong 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
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:
• Strong 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