Google AI Full Stack Developer

Google AI Full Stack Developer

CVS

Hartford, CT **MUST BE LOCAL TO THE AREA - ONSITE INTERVIEW WILL BE REQUIRED FOR 2nd ROUND. I do not want any surprises when asking the candidate to come onsite for an interview that they are travelling OR not in CT this week, etc.**

Hybrid

USC or GC ONLY

This team is REALLY tough. ROCKSTARS ONLY HERE WITH EXCEPTIONAL COMMUNICATION SKILLS, good camera connection for the interviews, Linked In with Photos and matching the the resume, ID's, copies of a bill to show they are local, etc

We are seeking to fill Google AI Full Stack Developer roles - 2 local to Hartford, CT

Start Date: As soon as possible

Duration of the engagement: 6+ months

Number of Roles: 2 local to Hartford, CT

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 (GCP)

1+ years working in Agile environments, with practical knowledge of DevOps principles and end-to-end software lifecycle

Preferred Qualifications

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.