Overview
On Site
Accepts corp to corp applications
Contract - months plu(s)
Skills
AI
NLP
Vertex
Conversational
Dialogflow
Job Details
We are seeking to fill Google AI Full Stack Developer roles Only local to Hartford, CT
Start Date: As soon as possible
Start Date: As soon as possible
Duration of the engagement: 6+ months
Number of Roles: 2 local to Hartford, CT
Position Summary
Position Summary
The Aetna IT Delivery organization, part of CVS Health's Data, Digital, Analytics, Technology (DDAT) division, is seeking a Conversational AI Engineer specializing in Google Conversational AI technologies and Retrieval Augmented Generation (RAG). You will drive the end-to-end user experience for a next-generation Conversational AI platform designed to support members and providers by accessing timely, accurate health insurance answers across digital channels.
In this role, you will architect, implement, and optimize rich conversational flows using Google's Conversational AI stack, while integrating enterprise data sources to deliver context-aware, trustworthy responses. You'll collaborate with product, UI/UX, and backend teams to define requirements, influence features, and ensure scalable, user-centric solutions.
Key Responsibilities
- Design and Develop Advanced Google AI Conversations Build and maintain dialog flows using Google Dialogflow CX, Google Vertex AI, or similar Google conversational platforms, with strong focus on contextual intent fulfillment.
- Implement Retrieval Augmented Generation (RAG) Integrate external knowledge bases and enterprise APIs with AI models to enable dynamic, contextually relevant, and reference-backed answers using RAG approaches.
- Apply Best Practices in Conversational AI Employ robust coding standards, NLP best practices, and reusable design patterns to ensure consistent and scalable solutions.
- Collaborate Across Functions Work closely with UI/UX designers, backend teams, and data engineers to define and implement APIs, data retrieval pipelines, and conversational triggers.
- End-to-End Chatbot Lifecycle Lead the design, development, testing, deployment, and ongoing maintenance of conversational agents, optimizing for user engagement and satisfaction.
- Integrate with Multiple Platforms Ensure seamless interactions across digital channels (web, mobile, voice), integrating with Google Cloud and enterprise APIs as required.
- Enhance Conversational Intelligence Use Google's advanced NLP, speech-to-text, and machine learning capabilities, and Large Language Models (LLMs) to refine accuracy, dialog flow, and natural language understanding.
- Continuous Learning and Innovation Stay abreast of emerging generative AI, conversational technologies, and industry best practices, supporting business development through technology-driven innovation.
- Speech Technologies Tune and enhance speech recognition and TTS models leveraging Google Cloud Speech-to-Text and related technologies, including advanced tagging (e.g., SSML).
Required Qualifications
3+ years software engineering experience delivering AI-enabled applications
2+ years hands-on chatbot development with Google Dialogflow CX, Vertex AI, or equivalent platforms (such as Amazon Lex, LivePerson, Kore.ai, IBM Watson)
2+ years applying NLP and training data best practices in production conversational AI settings
2+ years of experience with enterprise-scale AI/chatbot frameworks, including integration with backend data and API services
1+ years of experience with retrieval-augmented generation techniques (RAG) or integrating external knowledge sources into LLM-driven chatbots
1+ years of experience in CICD, Git, unit testing, and source code management workflows
1+ years familiarity with cloud development/deployment principles, ideally Google Cloud Platform (Google Cloud Platform)
1+ years working in Agile environments, with practical knowledge of DevOps principles and end-to-end software lifecycle
Backend (server-side) development experience in Java, Node.js, or Python
- Multi-language proficiency, with experience in Javascript/Typescript
- Prior work with Google Cloud Speech-to-Text, Vertex AI Search, or similar voice and information retrieval technologies
- Familiarity with SSML (Speech Synthesis Markup Language) tagging for TTS refinement
- Experience integrating unstructured data sources (e.g., document searching using semantic embeddings) with conversational agents
Education
Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience required.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.