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Conversational Ai Engineer Jobs (NOW HIRING)

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As a Product Manager - Conversational AI at ChatBotz.ai, you will play a pivotal role in driving ... Work closely with the engineering team to define technical requirements and ensure successful ...

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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 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 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 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 June 2026, with employment types broken down into 99% Full Time, and 1% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.
AI Engineer - LangGraph, Dialogflow, and Google Cloud - Schaumburg, IL - Contract opportunity

AI Engineer - LangGraph, Dialogflow, and Google Cloud - Schaumburg, IL - Contract opportunity

Zodiac Solutions

Schaumburg, IL • On-site

$59 - $76.50/hr

Contractor

Posted 20 days ago

Job description

Job Title: AI Engineer – LangGraph, Dialogflow, and Google Cloud

Location:  Schaumburg, IL - hybrid 3 days a week

Duration: 6 Months contract to hire

( preferably local candidates only )

We are seeking a highly skilled AI Engineer to design, develop, and deploy intelligent conversational and workflow automation systems using LangGraph, Google Dialogflow, and Google Cloud Platform (GCP). The ideal candidate will have strong experience building AI-driven solutions that integrate natural language understanding, context management, and multi-step logic orchestration.

You’ll collaborate closely with product managers, developers, and data teams to deliver scalable, efficient, and intuitive AI experiences through Google Chat and related platforms.

Key Responsibilities

  • Design, implement, and optimize conversational AI agents using LangGraph for workflow logic and Dialogflow (CX/ES) for dialogue management.
  • Integrate AI workflows with Google Chat to support automated conversations, task execution, and real-time user interaction.
  • Develop and maintain backend integrations with APIs, databases, and Google Cloud services such as Cloud Functions, Vertex AI, Pub/Sub, and Firestore.
  • Collaborate with cross-functional teams to define, test, and deploy new AI-driven features and improve existing dialogue flows.
  • Optimize system performance and scalability using GCP services and best practices in AI and cloud architecture.
  • Monitor and continuously improve AI accuracy through data-driven evaluation, logging, and fine-tuning of models and conversation paths.
  • Stay updated with the latest in conversational AI frameworks, Google Cloud tools, and LLM-based orchestration (LangChain, LangGraph, etc.).

Required Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or related field.
  • 8+ years of experience as an AI Engineer, Conversational AI Developer, or similar role.
  • Hands-on experience with LangGraph (or LangChain) for building LLM-powered flow orchestration.
  • Proven experience developing bots on Google Chat, Dialogflow CX/ES, and integrating workflows using Google Cloud Functions or REST APIs.
  • Solid understanding of Google Cloud Platform (GCP) components such as Vertex AI, BigQuery, Cloud Run, IAM, and API Gateway.
  • Strong coding skills in Python or Node.js, with experience in building and deploying AI or ML applications.
  • Familiarity with prompt engineering, LLM lifecycle management, and embedding/vector store integration.

Preferred Qualifications

  • Experience using Vertex AI Agent Builder or other Google Cloud AI tools.
  • Knowledge of LangGraph and flow-based orchestration for coordinating multiple AI tools and APIs.
  • Strong understanding of conversational design principles and UX for chat-based applications.
  • Exposure to LLMs (like Gemini, GPT, or Claude) and designing multi-turn interactive agents.
  • Google Cloud certification (e.g., Professional Cloud Developer, Machine Learning Engineer) is a plus.

Soft Skills

  • Excellent problem-solving and debugging abilities.
  • Strong communication and teamwork skills.
  • Ability to work independently and manage multiple projects simultaneously.
  • Curiosity and enthusiasm for AI research and applied innovation.
 
Thanks,
sanjay kumar
sanjay.kumar@zodiac-solutions.com
linkedin.com/in/sanjay-kumar-sann-841825172