Google AI Full Stack Developer in Hartford CT

Hartford, CT - USA

Monthly Salary: Not Disclosed

Posted on: 4 hours ago

Vacancies: 1 Vacancy

Job Summary

We are seeking to fill Google AI Full Stack Developer roles Only 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 Healths 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 Googles Conversational AI stack while integrating enterprise data sources to deliver context-aware trustworthy responses. Youll 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 Googles 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 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

Backend (server-side) development experience in Java 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

Bachelors degree in Computer Science Engineering or related field or equivalent experience required.

We are seeking to fill Google AI Full Stack Developer roles Only 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 Healths Data Digital Analytics...

We are seeking to fill Google AI Full Stack Developer roles Only 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

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 Googles 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).