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Ai Chatbot Developer Jobs in Dallas, TX (NOW HIRING)

VeridianTech

AI Architect Remote Role

Dallas, TX · On-site

$62.50 - $82.50/hr

This individual will partner closely with business stakeholders, engineering teams, data teams, and ... Architect sophisticated conversational AI/chatbot platforms capable of supporting complex workflows ...

New

Gartner

Sr Data Scientist

Irving, TX

Prompt Engineering, Context Engineering, Harness Engineering * Conversational AI, chatbot development, and dialogue systems * Natural Language Processing and text mining * Search and Recommendation ...

Gartner

Sr Data Scientist

Irving, TX · On-site

Prompt Engineering, Context Engineering, Harness Engineering * Conversational AI, chatbot development, and dialogue systems * Natural Language Processing and text mining * Search and Recommendation ...

GM Financial

Conversation Designer II

Arlington, TX · Hybrid

Experience in AI, chatbot/IVR strategy, conversation design, and optimization * Knowledge of Natural Language Processing and Prompt Engineering * Familiar with Agile principles and able to work ...

GM Financial

Conversation Designer II

Arlington, TX · On-site

Experience in AI, chatbot/IVR strategy, conversation design, and optimization * Knowledge of Natural Language Processing and Prompt Engineering * Familiar with Agile principles and able to work ...

Forhyre

Tech Lead - Conversational AI

Plano, TX · On-site

Design, develop, test, and deploy highly scalable and reliable chatbot solutions. * Ensure the ... Bachelor's degree in Computer Science, Engineering, or a related field. * Proven experience as a ...

Forhyre

Tech Lead - Conversational AI

Dallas, TX · On-site

Design, develop, test, and deploy highly scalable and reliable chatbot solutions. * Ensure the ... Bachelor's degree in Computer Science, Engineering, or a related field. * Proven experience as a ...

Equinix, Inc.

Senior Network Automation Engineer

Dallas, TX · On-site

$102K - $141K/yr

Design & Develop MCP Server and implement AI Chatbot interface for EAAS * Understand current ... Adopt AI/ML-powered developer tools (e.g., GitHub Copilot, Claude code, code generation assistants ...

New

Equinix

Senior Network Automation Engineer

Dallas, TX · Remote

$106K - $145K/yr

Design & Develop MCP Server and implement AI Chatbot interface for EAAS * Understand current ... Adopt AI/ML-powered developer tools (e.g., GitHub Copilot, Claude code, code generation assistants ...

New

DataBank

Enablement Engineer

Dallas, TX · On-site

The Enablement Engineer is a technical individual contributor responsible for implementing, testing ... AI chatbot technical build in Year 2. This role sits within the SEE team and reports to the Sr. ...

MSR Cosmos

Google Cloud ML Engineer

Dallas, TX · On-site

$55.25 - $73.75/hr

... developer to design, build, and deploy advanced conversational AI solutions on Google Cloud. You ... Solid understanding and practical application of MLOps best practices for chatbot pipelines ...

Photon

Gen AI Lead - TX

Irving, TX · On-site

$15.50 - $18.75/hr

Lead a team of Gen AI developers and specialists, providing mentorship, guidance, and fostering ... Experience in the chatbot, IVR, or banking domain. * Proven ability to build and manage high ...

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All JobsAi Chatbot Developer JobsAi Chatbot Developer Jobs in Dallas, TX

Ai Chatbot Developer information

See Dallas, TX salary details

$70.1K

$88.2K

$119K

How much do ai chatbot developer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for ai chatbot developer in Dallas, TX is $88,158.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,200.00 and $89,300.00 per year, depending on experience, location, and employer.

What does an AI Chatbot Developer do?

An AI Chatbot Developer designs, builds, and maintains intelligent conversational agents that can communicate with users through text or voice. They use artificial intelligence, natural language processing, and machine learning techniques to create chatbots capable of understanding and responding to user queries. Their responsibilities often include writing code, training chatbot models, integrating chatbots with various platforms, and improving bot performance based on user interactions.

What are the key skills and qualifications needed to thrive as an AI Chatbot Developer?

To thrive as an AI Chatbot Developer, you need strong programming skills (especially in Python or JavaScript), understanding of natural language processing (NLP), and a background in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), chatbot platforms (such as Dialogflow or Microsoft Bot Framework), and relevant APIs or cloud services is essential. Creative problem-solving, effective communication, and adaptability are important soft skills for designing engaging user experiences and addressing evolving requirements. These skills ensure robust, intelligent chatbot solutions that deliver value through seamless user interactions and continuous improvement.

What are some common challenges AI Chatbot Developers face when integrating chatbots with existing business systems?

One of the main challenges Ai Chatbot Developers encounter is ensuring seamless integration of chatbots with existing business platforms such as CRM, databases, or helpdesk software. This often requires deep understanding of APIs, data privacy regulations, and company-specific workflows. Developers must also ensure that the chatbot can accurately process and respond to user queries while securely accessing and updating relevant information. Collaboration with IT and business operations teams is key to addressing compatibility and security concerns during integration.

What is the difference between Ai Chatbot Developer vs AI Software Engineer?

AspectAi Chatbot DeveloperAI Software Engineer
CredentialsRelevant programming certifications, AI, NLP knowledgeComputer science degrees, AI certifications
Work EnvironmentDeveloping conversational interfaces, scripting, UI designBuilding AI models, algorithms, software systems
Industry UsageCustomer service, virtual assistants, chat platformsBroader AI applications across industries
Search/Comparison IntentFocus on chatbot-specific skills and toolsBroader AI development skills and projects

While both roles involve AI and programming, Ai Chatbot Developers specialize in creating conversational agents and chat interfaces, often focusing on NLP and UI design. AI Software Engineers work on developing a wide range of AI models and systems across various applications. The roles overlap in technical skills but differ in their primary focus and industry applications.

What cities near Dallas, TX are hiring for Ai Chatbot Developer jobs?

Cities near Dallas, TX with the most Ai Chatbot Developer job openings:

Ai Chatbot Developer jobs near you
Infographic showing various Ai Chatbot Developer job openings in Dallas, TX as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, and 3% Contract. Highlights an 69% Physical, 4% Hybrid, and 27% Remote job distribution, with an average salary of $88,158 per year, or $42.4 per hour.

AI Architect Remote Role

VeridianTech

Dallas, TX • On-site

$62.50 - $82.50/hr

Other

Posted 2 days ago

New

Job description

AI Architect Remote Role
For only EST or CST candidate
Position Overview
Core Technical Skills

Must Have:


Google Cloud Platform Generative AI LLMs Agentic AI Multi-Agent / A2A Systems Complex Chatbots / Conversational AI RAG Knowledge Graphs Machine Learning MCP Python Enterprise AI Architecture Document AI / Document Processing

linkedin As well
MUST COMPLETE ROPES ASSESSMENT
Ideal Candidate

This is not simply a hands-on AI development role. The successful candidate will be someone who can operate at both the strategic and technical architecture levels-working with leadership to define the AI vision while also going deep with engineering teams on how solutions should be designed and implemented.

They should be comfortable walking into an ambiguous business problem, leading the conversation, identifying the appropriate AI approach, and translating that vision into a scalable enterprise architecture and actionable technical roadmap.

We are seeking an experienced AI Solutions Architect to lead the strategy, architecture, and design of complex enterprise AI and Generative AI solutions. This individual will partner closely with business stakeholders, engineering teams, data teams, and leadership to translate business requirements into scalable AI architectures and drive technical conversations from concept through implementation.

The ideal candidate will have deep experience designing high-complexity conversational AI and chatbot solutions, including agentic AI, multi-agent architectures, and agent-to-agent (A2A) interactions. This role requires a strong combination of AI architecture, machine learning, cloud, data, and hands-on technical expertise.

Key Responsibilities
  • Lead the strategy, architecture, and technical design of enterprise AI, Generative AI, and Agentic AI solutions.
  • Architect sophisticated conversational AI/chatbot platforms capable of supporting complex workflows, reasoning, orchestration, and enterprise integrations.
  • Design agentic and multi-agent AI architectures, including agent-to-agent transactions, communication, orchestration, tool usage, and workflow execution.
  • Design and implement Retrieval-Augmented Generation (RAG) architectures leveraging enterprise structured and unstructured data.
  • Architect solutions utilizing knowledge graphs to improve contextual understanding, reasoning, relationships, and information retrieval.
  • Develop and guide machine learning and Generative AI solutions across enterprise use cases.
  • Design AI architectures leveraging Model Context Protocol (MCP) to securely connect AI agents and models with enterprise tools, systems, APIs, and data sources.
  • Architect and deploy AI/ML solutions within Google Cloud Platform (Google Cloud Platform), leveraging appropriate cloud-native AI, data, compute, and integration services.
  • Lead architecture discussions and technical strategy sessions with senior business and technology stakeholders.
  • Translate complex business requirements and technical documentation into clear AI solution designs, architecture patterns, roadmaps, and implementation strategies.
  • Evaluate AI technologies, models, frameworks, and architectural approaches and provide recommendations based on business and technical requirements.
  • Establish best practices around AI scalability, security, governance, performance, reliability, and responsible AI.
  • Provide technical leadership and architectural guidance to engineering, data science, machine learning, and platform teams.
  • Develop prototypes and reference implementations using Python to validate architectural concepts and AI capabilities.
Required Qualifications
  • Extensive experience as an AI Solutions Architect, AI Architect, ML Architect, or similar senior technical architecture role.
  • Strong experience architecting complex enterprise chatbot and conversational AI solutions.
  • Deep understanding of Agentic AI and multi-agent systems, including agent-to-agent (A2A) communication, orchestration, reasoning, tool calling, and autonomous workflows.
  • Strong hands-on experience with Generative AI and Large Language Models (LLMs).
  • Strong experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.
  • Experience with knowledge graphs, semantic relationships, graph-based retrieval, and/or knowledge-driven AI architectures.
  • Strong foundation in machine learning concepts, architectures, and production ML solutions.
  • Experience with Model Context Protocol (MCP) and integrating AI applications/agents with enterprise systems, APIs, tools, and data.
  • Deep experience with Google Cloud Platform (Google Cloud Platform) and building scalable AI/ML solutions in the Google Cloud Platform ecosystem.
  • Strong Python development experience for AI/ML applications, integrations, prototyping, and solution development.
  • Experience working with structured and unstructured enterprise data, including document ingestion, extraction, translation, summarization, and intelligent document processing.
  • Strong understanding of APIs, microservices, cloud architecture, data integration, security, and enterprise application architecture.
  • Ability to communicate complex AI concepts to both technical and non-technical stakeholders.
  • Demonstrated ability to drive AI strategy, influence architectural decisions, and lead technical conversations across multiple teams.

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