Conversational AI Engineer

Job Title: Sr. Developer – Google AI Full Stack / Conversational AI Engineer Internal Title: Program Manager Work Model: Hybrid Location: Onsite – Hartford, CT (USCTHARC01 Hartford - CT USA, CLT/RMT) Years of Experience: 10–14 years (Total: up to 14 years) Job Type: Business Associate (50CW00) Travel Required: No Subcontractor Allowed: Yes Certifications Required: None Job Summary The Aetna IT Delivery organization, part of CVS Health’s Data, Digital, Analytics, Technology (DDAT) division, is seeking a Conversational AI Engineer / Google AI Full Stack Developer for the YAVA project. You will be responsible for designing and delivering a next-generation Conversational AI platform to support members and providers by leveraging Google Conversational AI technologies and Retrieval Augmented Generation (RAG). You will own the end-to-end user experience and build scalable, context-aware conversational solutions. Required Experience • 10–14 years of total IT experience • Strong hands-on experience in Conversational AI and Generative AI • Experience working with Google Cloud Platform (GCP) and AI services Required Skills Technical Skills: • Amazon Lex • Kore.ai • Machine Learning • GCP (Google Cloud Platform) • Generative AI (e.g., GPT-3) • RAG (Retrieval Augmented Generation) (Nice to Have Skills: Not specifically mentioned.) Technology • Not Applicable (general AI / GCP / conversational platforms) Responsibilities Design & Develop Advanced Google AI Conversations • Build and maintain dialog flows using Google Dialogflow CX, Google Vertex AI, or similar Google conversational platforms • Focus on contextual intent handling and high-quality user interactions Implement Retrieval Augmented Generation (RAG) • Integrate external knowledge bases and enterprise APIs with AI models • Deliver dynamic, contextually relevant, and reference-backed responses Apply Best Practices in Conversational AI • Use robust coding standards, NLP best practices, and reusable design patterns • Ensure scalability, maintainability, and consistency across solutions Cross-Functional Collaboration • Work with Product, UI/UX, and Backend teams • Define requirements, influence features, and design APIs and data retrieval pipelines • Align conversational triggers with backend and data engineering workflows End-to-End Chatbot Lifecycle Ownership • Lead design, development, testing, deployment, and maintenance of conversational agents • Continuously optimize for user engagement, satisfaction, and performance Multi-Channel Integration • Ensure seamless experiences across web, mobile, and voice channels • Integrate solutions with Google Cloud services and enterprise APIs Enhance Conversational Intelligence • Use Google’s NLP, speech-to-text, machine learning, and LLMs • Improve accuracy, dialog flow, and natural language understanding Continuous Learning & Innovation • Stay current with emerging generative AI and conversational technologies • Contribute ideas and solutions that support technology-driven business innovation Speech Technologies • Tune and enhance speech recognition and text-to-speech (TTS) models • Work with Google Cloud Speech-to-Text and related technologies • Use advanced tagging such as SSML for better voice experiences