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Dialogflow Jobs in Atlanta, GA (NOW HIRING)

Navtech, Inc.

Google Contact Center AI

Alpharetta, GA · On-site

$15.75 - $21.50/hr

Deep knowledge of how NLU (natural language understanding) is used to implement Dialogflow conversations * Implementation of chat virtual agent * Implementation of voice virtual agent * Integrating ...

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Dialogflow information

See Atlanta, GA salary details

$19

$65

$90

How much do dialogflow jobs pay per hour?

As of Jul 27, 2026, the average hourly pay for dialogflow in Atlanta, GA is $65.27, according to ZipRecruiter salary data. Most workers in this role earn between $58.30 and $83.29 per hour, depending on experience, location, and employer.

What is a Dialogflow job?

A Dialogflow job typically involves designing, building, and optimizing conversational AI solutions using Google Dialogflow. Responsibilities may include creating intelligent chatbots, integrating natural language processing (NLP) models, and improving user interactions. Professionals in this field often work as chatbot developers, AI engineers, or conversational UX designers. Strong knowledge of machine learning, APIs, and cloud platforms is beneficial for this role.

What are the key skills and qualifications needed to thrive in the Dialogflow position, and why are they important?

To succeed as a Dialogflow Developer or Specialist, you need expertise in conversational AI design, strong programming skills (especially in JavaScript or Python), and experience with Natural Language Processing (NLP) frameworks. Familiarity with Google Cloud Platform, Dialogflow CX/ES, API integration, and relevant certifications such as Google Cloud Dialogflow certification are highly valuable. Excellent problem-solving abilities, communication skills, and attention to user experience will set you apart. These competencies are crucial for delivering robust, user-friendly chatbot solutions that align with client requirements and business goals.

What are the typical responsibilities of a Dialogflow Developer in a workday?

A Dialogflow Developer typically spends their day designing, building, and maintaining conversational agents and chatbots using Dialogflow. This includes creating intents and entities, integrating APIs, testing natural language models, and collaborating with UX designers and other engineers to enhance conversation flows. You may also be tasked with troubleshooting user issues, analyzing performance metrics, and optimizing chatbot performance based on user feedback. The role often requires teamwork across product, development, and customer support departments to ensure seamless virtual assistant solutions that meet business objectives.

What are the most commonly searched types of Dialogflow jobs in Atlanta, GA? The most popular types of Dialogflow jobs in Atlanta, GA are:
What are popular job titles related to Dialogflow jobs in Atlanta, GA? For Dialogflow jobs in Atlanta, GA, the most frequently searched job titles are:
What job categories do people searching Dialogflow jobs in Atlanta, GA look for? The top searched job categories for Dialogflow jobs in Atlanta, GA are:
Dialogflow jobs near you
Infographic showing various Dialogflow job openings in Atlanta, GA as of July 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $135,769 per year, or $65.3 per hour.
Conversational AI Engineer

Conversational AI Engineer

R2 Technologies Corporation

Alpharetta, GA • On-site

Full-time

Posted 27 days ago

Job description

Overview:
Description:
Our client is looking for a Conversational AI Engineer to design, implement, and enhance a conversational AI agent leveraging the latest advancements in Generative AI and Natural Language Processing (NLP).
This role will work closely with business stakeholders to understand user needs, analyze AI interactions, and develop intelligent, responsive chatbot experiences. The ideal candidate has experience with Dialogflow CX, Vertex AI, BigQuery, and Looker Studio, as well as a deep understanding of LLMs (Large Language Models), prompt engineering, and fine-tuning AI models.
Tasks:
Develop and optimize a Generative AI-powered virtual assistant to provide accurate, dynamic, and context-aware responses.
Leverage LLMs and fine-tuning techniques within Vertex AI for advanced conversational capabilities.
Implement and refine conversational experiences in Dialogflow CX, incorporating Playbooks and Tools for structured interactions.
Analyze chatbot performance using BigQuery and Looker Studio to identify areas for improvement and enhance response quality.
Create guided conversational flows and prompt engineering strategies to optimize AI responses.
Enhance AI reasoning and retrieval-augmented generation (RAG) techniques to improve the agent's ability to pull in relevant, up-to-date information.
Integrate Google Cloud Functions for seamless backend connectivity and automation.
Work with stakeholders to ensure AI solutions align with business goals and compliance requirements.
Monitor and iterate on AI model performance, implementing continual improvements based on user feedback and analytics.
Knowledge, Skills and Abilities Required:
Strong problem-solving skills and ability to work with both technical and non-technical stakeholders.
Skills Required:
Experience developing AI-powered chat bots or virtual assistants, preferably using Dialogflow CX and Vertex AI.
Strong understanding of Generative AI, LLMs, NLP, and prompt engineering techniques.
Proficiency in Google Cloud Services, including Vertex AI, BigQuery, Looker Studio, and Cloud Functions.
Familiarity with Dialogflow Playbooks and Tools for structured conversational AI development.
Experience analyzing AI performance metrics and improving model accuracy.
Ability to translate business needs into effective Generative AI solutions.
Bachelors or master's degree in computer science, Computer Information Systems, AI, or a related field
Skills Desired:
Familiarity with APIs, cloud security best practices, and AI ethics
Proficiency in Python or JavaScript for AI model integration and automation.
Experience with RAG-based AI approaches to improve knowledge retrieval in conversations.
Experience deploying infrastructure as code using Terraform.
Skills:
NLP

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