Conversational AI Engineer

Key Responsibilities:-
• Develop and optimize a Generative AI-powered virtual assistant to provide accurate, dynamic, and context-aware responses.
• Leverage LLMs and fine-tuning techniques within Vertex AI for advanced conversational capabilities.
• Implement and refine conversational experiences in Dialog flow CX, incorporating Playbooks and Tools for structured interactions.
• Analyze chatbot performance using Big Query and Looker Studio to identify areas for improvement and enhance response quality.
• Create guided conversational flows and prompt engineering strategies to optimize AI responses.
• Enhance AI reasoning and retrieval-augmented generation (RAG) techniques to improve the agent’s ability to pull in relevant, up-to-date information.
• Integrate Google Cloud Functions for seamless backend connectivity and automation.
• Work with stakeholders to ensure AI solutions align with business goals and compliance requirements.
• Monitor and iterate on AI model performance, implementing continual improvements based on user feedback and analytics.

 

Required Qualifications:-
• Bachelor’s or master’s degree in computer science, Computer Information Systems, AI, or a related field.
• Experience developing AI-powered chatbots or virtual assistants, preferably using Dialog flow CX and Vertex AI.
• Strong understanding of Generative AI, LLMs, NLP, and prompt engineering techniques.
• Proficiency in Google Cloud Services, including Vertex AI, Big Query, Looker Studio, and Cloud Functions.
• Familiarity with Dialog flow Playbooks and Tools for structured conversational AI development.
• Experience analyzing AI performance metrics and improving model accuracy.
• Ability to translate business needs into effective Generative AI solutions.
• Strong problem-solving skills and ability to work with both technical and non-technical stakeholders.

 

Preferred Qualifications:-
• Familiarity with APIs, cloud security best practices, and AI ethics.
• Proficiency in Python or JavaScript for AI model integration and automation.
• Experience with RAG-based AI approaches to improve knowledge retrieval in conversations.
• Experience deploying infrastructure as code using Terraform.