Job Title: Google AI Full Stack Developer
Location: Hartford CT (Onsite)- Local candidates
Duration: 6 Months (Contract to Hire)
Interview: Video Interview
Visa- USC/ GC/ GC-EAD Only
Job Description
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 fulfilment.
- 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 Dialog flow 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 (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 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
Job Title: Google AI Full Stack Developer Location: Hartford CT (Onsite)- Local candidates Duration: 6 Months (Contract to Hire) Interview: Video Interview Visa- USC/ GC/ GC-EAD Only Job Description Key Responsibilities: Design and Develop Advanced Google AI Conversations Build and maintain ...
Job Title: Google AI Full Stack Developer
Location: Hartford CT (Onsite)- Local candidates
Duration: 6 Months (Contract to Hire)
Interview: Video Interview
Visa- USC/ GC/ GC-EAD Only
Job Description
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 fulfilment.
- 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 Dialog flow 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 (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 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
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