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Conversational Ai Engineer Jobs (NOW HIRING)

Collabera LLC

Conversational AI Engineer

Dallas, TX

IVA Engineer (Conversational AI Engineer (IVA / Voice / IVR) Locations: Baltimore MD, Dallas TX - Any one location Schedule: Hybrid Day to day: * Design intent taxonomy, utterances, and dialogue ...

Saransh Inc

Conversational AI Developer

Irving, TX · On-site

Conversational AI Developer Locations: Irving/Dallas, Texas & Jacksonville Florida Duration: Long Term Day to Day job Duties: * Develop and implement conversational AI solutions: Design, build, and ...

Tror AI for everyone

Java AI Engineer

Farmington Hills, MI · On-site

$51 - $69.75/hr

JOB Title: Java AI Engineer Location: Farmington Hills, MI (Hybrid) Hiring Type: Contract Note ... Prior experience with building Agentic AI solutions, conversational AI chatbots or summarization ...

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Conversational Ai Engineer information

What are the key skills and qualifications needed to thrive as a Conversational AI Engineer, and why are they important?

To thrive as a Conversational AI Engineer, you need strong programming skills (such as Python), a background in natural language processing (NLP), and a degree in computer science or a related field. Familiarity with machine learning frameworks, chatbot platforms, and cloud services like AWS or Google Cloud is typically required, along with experience in tools such as TensorFlow or Rasa. Excellent problem-solving abilities, creativity, and clear communication help engineers design effective, user-friendly conversational systems. These skills ensure the development of robust, scalable, and intuitive AI solutions that meet user needs and business goals.

What are some common challenges Conversational AI Engineers face when deploying chatbots in production environments?

Conversational AI Engineers often encounter challenges such as ensuring chatbot robustness in handling diverse user inputs and maintaining natural, contextually relevant conversations. Managing scalability and latency is also crucial, as chatbots must perform efficiently under varying loads. Additionally, integrating with legacy systems and safeguarding user data privacy require careful coordination with DevOps and security teams. Continuous model monitoring and updating are essential to keep responses accurate and aligned with user expectations.

What is a Conversational AI Engineer?

A Conversational AI Engineer is a technology professional who designs, develops, and maintains systems that enable computers to interact with humans using natural language. They work on building chatbots, virtual assistants, and voice-enabled applications by leveraging natural language processing (NLP), machine learning, and AI frameworks. Their responsibilities include training language models, optimizing conversation flows, integrating with APIs, and ensuring the overall performance and accuracy of conversational systems. These engineers collaborate with data scientists, UX designers, and software developers to create seamless and intuitive AI-driven user experiences.

What is the difference between Conversational Ai Engineer vs Chatbot Developer?

AspectConversational Ai EngineerChatbot Developer
Required CredentialsBachelor's in CS, AI, or related field; experience with NLP and machine learningTypically programming skills; may have similar technical background
Work EnvironmentCollaborates on AI models, NLP, and user experience designFocuses on building and deploying chatbot interfaces
Employer & Industry UsageTech companies, AI startups, large enterprises integrating conversational AICustomer service, marketing, and sales sectors
Search & Comparison IntentUnderstanding roles in AI development, advanced conversational systemsBuilding specific chatbot applications

While both roles involve creating conversational interfaces, a Conversational Ai Engineer focuses on developing advanced AI models and NLP systems, whereas a Chatbot Developer primarily builds and deploys chatbot applications. The engineer's role is broader, often involving AI research and integration, while the developer concentrates on implementation and user interaction design.

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Conversational Ai Engineer jobs near you
Infographic showing various Conversational Ai Engineer job openings in the United States as of May 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 84% Physical, 5% Hybrid, and 11% Remote job distribution.
Conversational AI Engineer

Conversational AI Engineer

R2 Technologies

Alpharetta, GA • On-site, Remote

Other

Posted 14 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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