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conversational AI Engineer
- Connecticut, United States
- Connecticut, United States
About
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
- 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
Languages
- English
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