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Conversational Ai Developer Jobs in Texas (NOW HIRING)

Smash CR

Director of AI/ML (P-161)

Flower Mound, TX · On-site

Lead and mentor teams of AI engineers, ML engineers, and automation developers. * Design scalable ... Lead adoption of Databricks AI capabilities including MLflow, model serving, and conversational AI ...

Smash CR

Director of AI/ML (P-161)

Flower Mound, TX · On-site

Lead and mentor teams of AI engineers, ML engineers, and automation developers. * Design scalable ... Lead adoption of Databricks AI capabilities including MLflow, model serving, and conversational AI ...

Photon

AI Enabled Engineer - Python, Java

Dallas, TX · On-site

Integrate Large Language Models (LLMs), conversational AI frameworks, and third-party AI services ... Strong programming experience in Python and Java . * Proven experience in building intelligent ...

Photon

Gen AI Engineer -McKinney, TX

Dallas, TX · On-site

Ensure the prompts are intuitive for a productive conversation to elicit desired responses and ... Ensure seamless integration of prompt engineering strategies into existing AI systems. * Develop ...

Photon

Conversational Designer | Dallas

Dallas, TX · On-site

... AI systems. You will collaborate with cross-functional teams including developers, UX designers, and product managers to design and implement conversational experiences that meet the needs of users.

Natsoft Corporation

Sierra.ai Consultant

Dallas, TX · On-site

Job Summary (List Format): - 3 to 4 years of experience in production-grade Generative AI (GenAI) and Conversational AI implementations - Proficient in React, TypeScript, and/or Go programming ...

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Conversational Ai Developer information

What are the key skills and qualifications needed to thrive as a conversational AI developer?

To thrive as a Conversational AI Developer, you need a solid background in computer science, natural language processing (NLP), and machine learning, often supported by a relevant degree or certifications. Familiarity with tools like Python, TensorFlow, NLP libraries (such as spaCy or NLTK), and conversational platforms (like Dialogflow or Microsoft Bot Framework) is typically required. Strong problem-solving abilities, creativity, and effective communication skills help developers design intuitive and engaging conversational experiences. These skills are crucial for building AI systems that understand and respond accurately to human language, ensuring user satisfaction and business value.

What is a conversational AI developer?

A Conversational AI Developer is a professional who designs, builds, and maintains artificial intelligence systems that enable computers to interact with humans using natural language. These developers create chatbots, virtual assistants, and voice-enabled applications that can understand and respond to user input in a conversational manner. Their work often involves programming, natural language processing (NLP), machine learning, and integrating AI systems with various platforms or devices. They play a key role in improving user experiences through more intuitive, human-like interactions with technology.

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

AspectConversational Ai DeveloperChatbot Developer
Required CredentialsProgramming skills, AI/machine learning knowledge, NLP expertiseProgramming skills, basic AI understanding, scripting
Work EnvironmentTech companies, AI startups, enterprise AI teamsCustomer service, marketing, small to medium businesses
Industry UsageDevelops complex conversational systems with AI capabilitiesBuilds rule-based or simple chatbots for specific tasks
Search & Comparison IntentUnderstanding AI-driven conversational systemsCreating basic automated chat interactions

Conversational Ai Developers focus on building advanced, AI-powered conversational systems using NLP and machine learning, often working in tech or enterprise environments. Chatbot Developers typically create rule-based or simple chatbots for customer service or marketing, with less emphasis on AI complexity. While both roles involve programming and scripting, Conversational Ai Developers require deeper AI and NLP expertise for sophisticated interactions.

What are some common challenges conversational AI developers face when optimizing chatbot performance?

Conversational AI Developers often encounter challenges such as accurately interpreting user intent, handling ambiguous or unexpected queries, and maintaining natural, engaging dialogue flows. Balancing the need for robust natural language understanding with system efficiency and scalability is also key. Additionally, integrating the chatbot with existing platforms and ensuring data privacy can require careful planning and cross-functional collaboration.
What are popular job titles related to Conversational Ai Developer jobs in Texas? For Conversational Ai Developer jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Conversational Ai Developer jobs in Texas look for? The top searched job categories for Conversational Ai Developer jobs in Texas are:
What cities in Texas are hiring for Conversational Ai Developer jobs? Cities in Texas with the most Conversational Ai Developer job openings:
Conversational Ai Developer jobs near you
Infographic showing various Conversational Ai Developer job openings in Texas as of August 2026, with employment types broken down into 73% Full Time, 23% Part Time, and 4% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution.

Director of AI/ML (P-161)

Smash CR

Flower Mound, TX • On-site

Full-time

Re-posted 28 days ago

Job description

SMASH, Who we are?
We believe in long-lasting relationships with our talent. We invest time getting to know them and understanding what they seek as their professional next step.
We aim to find the perfect match. As agents, we pair our talent with our US clients, not only by their technical skills but as a cultural fit. Our core competency is to find the right talent fast.
This role is available to candidates located within the United States. Applicants must be U.S. citizens or hold a valid U.S. work authorization to be considered.
Hybrid role: onsite 2 days per week. Flower Mound, TX
Role summary
You will lead the enterprise AI/ML and intelligent automation strategy, driving the design and operationalization of scalable AI solutions across the organization's data platform. This role combines technical leadership, AI architecture expertise, and cross-functional collaboration to deliver machine learning, generative AI, multi-agent systems, and automation initiatives that create measurable business value.
Responsibilities
  • Define and execute the enterprise AI/ML and intelligent automation strategy.
  • Lead and mentor teams of AI engineers, ML engineers, and automation developers.
  • Design scalable, secure, and governed AI architectures using Databricks and Microsoft technologies.
  • Drive implementation of machine learning, generative AI, and multi-agent orchestration solutions.
  • Oversee development and deployment of AI-powered automation initiatives using Microsoft Power Automate and Copilot technologies.
  • Collaborate with Data Engineering, Reporting, and business teams to operationalize AI capabilities.
  • Implement AI governance, model lifecycle management, and responsible AI best practices.
  • Lead adoption of Databricks AI capabilities including MLflow, model serving, and conversational AI solutions.
  • Integrate AI and automation systems with enterprise applications such as ERP, CRM, and logistics platforms.
  • Establish KPIs and performance metrics to measure AI and automation impact.
  • Drive continuous innovation and evaluate emerging AI technologies and frameworks.
  • Communicate AI strategy, risks, and business outcomes to executive stakeholders.

Requirements - Must-haves
  • Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field (or equivalent experience).
  • 10+ years of experience in AI, machine learning, automation, or related technical domains.
  • 5+ years of leadership experience managing technical or engineering teams.
  • Experience leading enterprise AI and automation initiatives using Databricks and Microsoft technologies.
  • Strong expertise in enterprise AI architecture and machine learning platform design.
  • Experience implementing generative AI and agent-based systems.
  • Hands-on experience with Databricks AI capabilities including MLflow and model serving.
  • Experience integrating AI capabilities with Microsoft Copilot platforms.
  • Strong communication, stakeholder management, and leadership skills.
  • Ability to drive scalable, secure, and governed AI solutions.

Nice-to-haves (optional)
  • Experience with Microsoft Power Automate and robotic process automation (RPA).
  • Experience with conversational AI platforms such as Databricks Genie.
  • Experience implementing multi-agent orchestration frameworks.
  • Experience integrating AI systems with ERP, CRM, or logistics platforms.
  • Experience with AI-powered image or video processing technologies.
  • 12-15 years of progressive experience in AI engineering or enterprise data platforms.

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