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Ai Coder Jobs in Texas (NOW HIRING)

Userpilot, Inc

Software Engineer (AI-Native)

Austin, TX · On-site

$100 - $130/hr

Review code for architectural consistency and maintainability across the stack - including making ... AI features: experience building or integrating LLM-powered features - streaming responses, AI ...

Varsity Tutors

Vibe Coding Tutor

Dallas, TX · Remote

$18 - $40/hr

... Vibe Coding tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Varsity Tutors

Vibe Coding Tutor

Lubbock, TX · Remote

$18 - $40/hr

... Vibe Coding tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Varsity Tutors

Vibe Coding Tutor

El Paso, TX · Remote

$18 - $40/hr

... Vibe Coding tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

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All JobsAi Coder JobsAi Coder Jobs in Texas

Ai Coder information

See Texas salary details

$14

$25

$40

How much do ai coder jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for ai coder in Texas is $25.61, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $32.26 per hour, depending on experience, location, and employer.

What types of projects do AI coders typically work on, and how does project collaboration usually happen?

AI Coders are often involved in developing machine learning models, creating data pipelines, and integrating AI solutions into existing products. Collaboration is a key part of the role, with AI Coders working closely with data scientists, software engineers, and product managers to translate business needs into technical solutions. Most teams use agile methodologies, daily stand-ups, and collaborative platforms like GitHub or Jira to coordinate tasks and track progress. This structure ensures that AI Coders receive frequent feedback and can contribute ideas throughout the development cycle.

What is an AI coder?

AI Coders are professionals who develop, implement, and maintain artificial intelligence (AI) systems and applications. They use programming languages such as Python, Java, and R to write code that enables machines to perform tasks that typically require human intelligence, such as learning, reasoning, and problem-solving. AI Coders often work with machine learning models, neural networks, and large datasets to create intelligent solutions for various industries. Their work can range from building chatbots and recommendation systems to designing complex algorithms for automation.

What is the difference between Ai Coder vs Data Scientist?

AspectAi CoderData Scientist
Required CredentialsProgramming skills, knowledge of AI frameworks, certifications in AI/MLStatistics, programming, data analysis certifications
Work EnvironmentSoftware development teams, AI research labsData analysis teams, research environments
Employer & Industry UsageTech companies, AI startups, R&D departmentsFinance, healthcare, marketing, tech firms

While both roles involve working with data and algorithms, Ai Coders primarily focus on developing AI models and coding AI solutions, whereas Data Scientists analyze data to extract insights and inform business decisions. Ai Coders are more involved in software development, while Data Scientists emphasize statistical analysis and data interpretation.

What are the key skills and qualifications needed to thrive as an AI coder, and why are they important?

To thrive as an AI Coder, you need strong programming skills (especially in Python), a solid understanding of machine learning concepts, and typically a degree in computer science or a related field. Familiarity with AI frameworks like TensorFlow or PyTorch, as well as experience with version control systems such as Git, is essential. Strong problem-solving abilities, attention to detail, and effective communication help you collaborate with teams and explain complex solutions. These skills and qualities are crucial for developing, optimizing, and maintaining reliable AI models that address real-world challenges.

What are popular job titles related to Ai Coder jobs in Texas?

For Ai Coder jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Ai Coder jobs in Texas look for?

The top searched job categories for Ai Coder jobs in Texas are:

What cities in Texas are hiring for Ai Coder jobs?

Cities in Texas with the most Ai Coder job openings:

Ai Coder jobs near you
Infographic showing various Ai Coder job openings in Texas as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 72% Physical, 3% Hybrid, and 25% Remote job distribution, with an average salary of $53,274 per year, or $25.6 per hour.

Principal AI Software Engineering Lead / IT Architect 3

3Core Systems, Inc

Irving, TX • On-site

$180 - $240/hr

Other

Posted 10 days ago

Job description

Principal AI Software Engineering Lead / IT Architect 3

Irving, United States | Posted on 08/03/2026

Role:Principal AI Software Engineering Lead / IT Architect 3

Location: Irving, TX (Hybrid onsite for 3 days/week)

Contract: 12 Months Contract

Position’sContributions to Work Group:

Seeking a Principal AI Software Engineering Lead todrive adoption of AI-powered software engineering platforms and Agenticdevelopment capabilities across enterprise engineering teams.

Primary focus is AI-assisted software development, engineering productivitytransformation, developer tooling strategy, and autonomous engineeringworkflows leveraging platforms such as Cursor, Claude Code, GitHub Copilot, andemerging AI coding agents.

This role will establish AI engineering standards, evaluation frameworks,governance, and best practices while partnering with engineering teams toaccelerate software delivery, improve quality, and enhance developerproductivity.

Strong experience in software architecture, cloud-native platforms, backendengineering, distributed systems, and AI-assisted development workflows isrequired.

Key focus areas:
  • Agentic Software Development &Specification-Driven Development
  • Engineering Productivity & DeveloperExperience
  • Software Architecture & Technical Leadership
  • AI Evaluation, Governance & AdoptionStrategy
  • Software Quality, Security & SDLCModernization
Why this Role?

Join client's AI Engineering Transformation journey and help define howsoftware is built in the age of AI. In this role, you will lead the evaluation,adoption, and scaling of next-generation AI software engineering platforms,including Cursor, Claude Code, GitHub Copilot, and emerging Agentic developmentcapabilities.

You will work closely with engineering teams across to establish AI-assisteddevelopment standards, improve developer productivity, accelerate softwaredelivery, and shape the future of software engineering at client.

This role offers a unique opportunity to influence engineering strategy, driveAI-native development practices, evaluate cutting-edge technologies, and helptransform how teams design, build, test, and maintain software. You'll tacklecomplex engineering challenges, partner with senior technical leaders, and playa key role in defining Client's long-term AI software engineering vision.

Typical Day or Week in the Role Typical Task Breakdown
  • Evaluate and benchmark AI software engineeringplatforms including Cursor, Claude Code, GitHub Copilot, and emerging agenticdevelopment tools.
  • Define and implement AI-assisted softwareengineering best practices, standards, governance, and adoption frameworks.
  • Partner with engineering teams to identify andexecute high-value AI pilot initiatives across Atlas, Physical AI, andenterprise software development.
  • Design and promote Agentic developmentworkflows, specification-driven development, and autonomous engineeringpractices.
  • Measure and analyze developer productivity,software quality, SDLC efficiency, and engineering outcomes using data-drivenmetrics.
  • Create reference architectures, implementationpatterns, and engineering guidance for AI-native software development.
  • Work closely with software architects,engineering managers, product teams, and platform teams to integrate AIcapabilities into the development lifecycle.
  • Evaluate security, compliance, and governanceconsiderations related to AI coding tools and developer workflows.
  • Mentor engineering teams on effective use ofAI-powered development tools and modern software engineering practices.
  • Drive continuous improvement initiatives focusedon accelerating delivery velocity, improving code quality, reducing technicaldebt, and enhancing developer experience.
  • Collaborate with vendors, strategic partners,and internal stakeholders to assess emerging AI engineering capabilities andindustry best practices.
  • Contribute to engineering strategy, roadmapplanning, technology selection, and long-term AI transformation initiativesacross client.
Interaction with Team
  • Partner closely with Engineering Directors,Engineering Managers, Principal Engineers, Architects, and Technical Leads todefine and execute AI software engineering strategy.
  • Collaborate with software development teamsacross Atlas, Physical AI, Autonomy Services, and enterprise engineeringorganizations to evaluate, pilot, and scale AI-assisted developmentcapabilities.
  • Work with Product Owners, Product Managers, andbusiness stakeholders to identify high-value engineering productivityopportunities and prioritize adoption initiatives.
  • Partner with DevOps, Platform Engineering,Cybersecurity, and Enterprise Architecture teams to establish governance,security, compliance, and operational standards for AI coding platforms.
  • Engage with engineering leadership to definesuccess metrics, measure outcomes, and communicate the impact of AI-assistedsoftware development initiatives.
  • Collaborate with external vendors and strategicpartners, including AI platform providers, to evaluate emerging technologiesand influence product direction.
  • Lead technical workshops, architecturediscussions, proof-of-concepts, and engineering enablement activities acrossmultiple organizations.
  • Mentor engineers and technical leaders onAI-native development practices, agentic workflows, and modern softwareengineering techniques.
  • Present recommendations, findings, pilotresults, and strategic roadmaps to senior leadership and executivestakeholders.
Team Structure

Individual contributor, work with different stakeholders across enterprise

Work environment: Office

Education & Experience Required
  • Years of experience: 5+
  • Degree requirement: Masters or Bachelor's degreein Computer Science, Software Engineering
  • Master's degree in Computer Science, SoftwareEngineering with 3 Yrs. of Exp
  • Associate's degree with 9 years' experience
  • Do you accept internships as job experience: No
  • Are there past or additional job titles or roles that would provide comparable background to this role: N/A
Top 3 Skills
  • AI-Assisted Software Engineering & DeveloperProductivity
  • Technical Leadership, Architecture & Engineering Transformation
Additional Technical Skills

(Required)

  • Cursor, Claude Code, GitHub Copilot or similarAI coding tools
  • Java/Spring Boot and Python development
  • Software architecture and engineering bestpractices
  • Prompt engineering and Agentic developmentworkflows
  • Engineering metrics and productivity measurement
  • Robotics, Physical AI, Simulation or DigitalTwin exposure
  • AWS/Azure cloud platforms
  • Developer experience platforms and DevOps
Soft Skills
  • Strong problem-solving and analytical skills
  • Ability to work effectively in agile scrum teams
  • Strong verbal and written communication skills
  • Collaboration across distributed andcross-functional teams
  • Ability to work in ambiguous and evolvingenvironments
  • Ownership mindset with accountability fordelivery
  • Strong technical documentation skills
  • Experience mentoring junior engineers
  • Technical leadership and design reviewexperience
  • Stakeholder management and vendor collaboration
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