About the role
P1 C3 TSTS Experience
Experience
At least 5+ years relevant technical work experience, in developing and implementing Conversational AI. And Overall experience above 8 years
Technical Skills
Expertise in prompt engineering to guide LLM-based customer interactions
Strong understanding of Conversational AI frameworks, IVR, and chat-based interactions
Experience defining rules, air-gapping mechanisms, and conversation guidelines to control LLM behavior
Ability to craft structured prompts for handling customer queries in telecom and contact center environments
Understanding of NLU, intent recognition, and contextual flow management
Experience in fine-tuning conversation flows while adhering to compliance and security standards
Collaborate with cross-functional teams to design, develop, and deploy conversational AI applications using Kore AI, across IVR, chat, and voice platforms.
Design effective, structured prompts that guide LLM responses while maintaining accuracy, consistency, and compliance
Develop and enforce air-gapping mechanisms to prevent undesired or off-topic responses
Define and document rules, guidelines, and guardrails for LLM-based interactions
Optimize multi-turn conversations to ensure seamless IVR and chat experiences
Collaborate with CX, product, and AI teams to refine conversational logic
Conduct A/B testing and performance analysis to improve LLM-generated responses
Good to have skills
Knowledge of machine learning algorithms and techniques.
Strong problem-solving skills and attention to detail.
Excellent communication and collaboration abilities.
Implementation of best practices and coding standards in conversational AI development, ensuring scalability and maintainability.
Stay updated with the latest trends in Conversational AI and Generative AI technologies, contributing to continuous improvement.
Knowledge in testing, debugging, and performance optimization of conversational AI applications.
Knowledge of telecom industry use cases, BSS, and IVR workflows
Experience in testing and optimizing LLM outputs for customer-facing applications
Strong analytical mindset with attention to detail
Ability to adapt prompt strategies based on business and user requirements
Familiarity with LLM safety, compliance, and ethical AI practices
