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Ai Application Developer Jobs in Texas (NOW HIRING)

Application Developer

San Antonio, TX ยท On-site

$80 - $110/hr

As an application developer for SWBC, you have the ability to work supportive environment that ... Experience designing or integrating agentic AI solutions, including taskโ€oriented or autonomous ...

As an application developer for SWBC, you have the ability to work supportive environment that ... Experience designing or integrating agentic AI solutions, including taskoriented or autonomous ...

As an application developer for SWBC, you have the ability to work supportive environment that ... Familiarity with AI-assisted development tools and generative AI platforms, such as Anthropic ...

Build and maintain AIP Analyst functions and other AI-powered capabilities to enhance application ... Collaborate with data engineering teams to ensure data flows properly from backing datasets into ...

Senior Application Developer

Dallas, TX

$95K - $130K/yr

The Senior Application Developer will be responsible for designing, developing, and maintaining ... Experience with AI technologies and frameworks. Preferred Qualifications: * 3-5 years React Native ...

Showing results 21-40

Ai Application Developer information

See Texas salary details

$15

$49

$79

How much do ai application developer jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for ai application developer in Texas is $49.04, according to ZipRecruiter salary data. Most workers in this role earn between $39.42 and $56.44 per hour, depending on experience, location, and employer.

What is an AI application developer?

An AI Application Developer is a professional who designs, builds, and maintains software applications that leverage artificial intelligence technologies. They work with programming languages, machine learning frameworks, and data to create intelligent systems such as chatbots, recommendation engines, or image recognition tools. AI Application Developers collaborate with data scientists and other engineers to integrate AI models into applications, ensuring they function efficiently and meet user needs. Their work spans industries like healthcare, finance, and retail, driving innovation through automation and smart solutions.

What skills and qualifications are needed to thrive as an AI application developer?

To thrive as an AI Application Developer, you need strong programming skills (especially in Python or Java), a solid understanding of machine learning concepts, and a relevant degree such as computer science or data science. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (AWS, Azure, or GCP), and certifications in AI or data science are highly valued. Creative problem-solving, collaboration, and effective communication help developers translate business needs into practical AI solutions. These skills and qualities are crucial for building robust, scalable AI applications that deliver real-world value.

How do AI application developers typically collaborate with data scientists and product managers during a project?

AI Application Developers often work closely with data scientists to integrate machine learning models into user-facing applications, ensuring the models function efficiently within production systems. Collaboration with product managers is also key, as developers help translate business requirements into technical solutions and provide feedback on feasibility and timelines. Regular cross-functional meetings and code reviews are common, fostering a collaborative environment that drives innovative and effective AI-powered products.

What is the difference between Ai Application Developer vs Data Scientist?

AspectAi Application DeveloperData Scientist
Required SkillsProgramming, AI frameworks, software developmentStatistics, data analysis, machine learning
Work EnvironmentSoftware development teams, tech companiesResearch labs, analytics teams
Common CertificationsAI certifications, programming coursesData science certifications, statistical credentials

While both roles involve AI and data, an Ai Application Developer primarily focuses on designing and building AI-powered applications using programming and AI frameworks. In contrast, a Data Scientist analyzes data to extract insights and build models, often working more on data analysis and statistical modeling. Both roles are essential in tech industries but serve different functions within AI projects.

How to become an AI application developer?

To become an AI application developer, you should gain a strong foundation in programming languages such as Python or Java, learn machine learning frameworks like TensorFlow or PyTorch, and develop skills in data analysis and algorithms. Earning relevant certifications or degrees in computer science, artificial intelligence, or related fields can also enhance your qualifications and job prospects.

What does an AI application developer do?

An AI application developer designs, builds, and maintains software applications that incorporate artificial intelligence and machine learning algorithms. They work with programming languages like Python or Java, utilize AI frameworks such as TensorFlow or PyTorch, and often collaborate with data scientists to implement intelligent features in products or services.

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

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

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

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

What cities in Texas are hiring for Ai Application Developer jobs?

Cities in Texas with the most Ai Application Developer job openings:

Infographic showing various Ai Application Developer job openings in Texas as of August 2026, with employment types broken down into 79% Full Time, 17% Part Time, and 4% Contract. Highlights an 91% Physical, 3% Hybrid, and 6% Remote job distribution, with an average salary of $102,007 per year, or $49 per hour.

Senior AI Application Engineer (Remote Opportunity)

Veterans EZ Info Inc

Dallas, TX โ€ข On-site

$140 - $180/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 4 days ago


Job description

VetsEZ is seeking a Senior AI Application Engineer to design, develop, and implement enterprise Artificial Intelligence (AI) solutions supporting the Department of Veterans Affairs (VA). The initial assignment will support the Joint Longitudinal Viewer (JLV) AI Summarization initiative, delivering a secure, governed AI-assisted search and summarization capability within an approved test environment utilizing Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and Amazon Bedrock, while supporting clinical evaluation and future production readiness.

Working closely with AI Solution Architects, Product Owners, cybersecurity teams, DevSecOps engineers, and clinical stakeholders, this individual will develop secure, scalable, and maintainable AI-powered applications that integrate seamlessly with existing enterprise healthcare systems while ensuring compliance with Federal security, privacy, and AI governance requirements.

Responsibilities
  • Design, develop, and implement enterprise AI applications utilizing Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG).
  • Develop AI-assisted search, summarization, and question-answering capabilities using Amazon Bedrock.
  • Build reusable AI services supporting prompt orchestration, document retrieval, and response generation.
  • Implement prompt engineering and source-grounding strategies to improve AI accuracy, consistency, traceability, and clinical relevance, including source links that support human verification.
  • Optimize AI performance while balancing response quality, latency, and operational cost.
  • Design and develop secure, scalable cloud-native applications utilizing modern software engineering practices.
  • Develop RESTful APIs and backend services supporting AI capabilities and enterprise integrations.
  • Implement approved document retrieval, vector search, and semantic search capabilities within the selected patient context and CHSD document set.
  • Develop automated unit, integration, and functional tests and repeatable AI evaluations for groundedness, retrieval quality, and clinical relevance supporting AI-enabled applications.
  • Troubleshoot software defects, optimize application performance, and support activities within the approved test environment and for future production readiness.
  • Integrate AI capabilities into existing enterprise healthcare applications and clinical workflows.
  • Develop secure interfaces utilizing REST APIs and modern integration patterns.
  • Support interoperability utilizing healthcare standards including FHIR, HL7, and CCD.
  • Collaborate with Solution Architects and engineering teams to implement scalable and maintainable application designs.
  • Participate in code reviews and promote software engineering best practices across the development team.
  • Develop secure software in accordance with Federal cybersecurity and privacy requirements, including approved data-retention and purge controls.
  • Support CI/CD pipelines, automated deployments, and cloud-native operational practices.
  • Implement logging, monitoring, audit capabilities, and operational telemetry, including model and prompt version tracking, usage and cost monitoring, and controls to detect model, prompt, retrieval, and data drift.
  • Support application security scanning, vulnerability remediation, and activities within the approved test environment and for future production readiness.
  • Incorporate Responsible AI, Human-in-the-Loop (HITL), and AI governance principles into application development.
  • Collaborate with architects, product owners, clinicians, cybersecurity teams, and Government stakeholders throughout the software development lifecycle.
  • Participate in Agile ceremonies including Sprint Planning, backlog refinement, Sprint Reviews, and Retrospectives.
  • Contribute to technical documentation, implementation guides, and software design artifacts.
  • Present technical solutions and implementation approaches to project leadership and stakeholders.
Requirements
  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, Artificial Intelligence, Data Science, or a related technical field, or equivalent experience.
  • 8+ years developing enterprise software applications.
  • 5+ years developing cloud-native applications utilizing AWS or comparable cloud platforms.
  • Demonstrated experience developing Artificial Intelligence, Machine Learning, or Generative AI solutions.
  • Experience implementing applications utilizing Amazon Bedrock or similar enterprise AI platforms.
  • Experience developing enterprise REST APIs and cloud-native application services.
  • Amazon Bedrock and AWS cloud services
  • Large Language Models (LLMs)
  • Retrieval-Augmented Generation (RAG)
  • Prompt engineering and AI evaluation
  • Python, Java, or C#
  • REST APIs and JSON
  • Vector databases, embeddings, and semantic search
  • Git, CI/CD, and DevSecOps
  • Healthcare interoperability (FHIR, HL7, CCD)
Additional Qualifications
  • Strong understanding of modern software engineering principles and cloud-native application development.
  • Experience developing scalable, secure, and maintainable enterprise applications.
  • Excellent analytical, troubleshooting, and problem-solving skills.
  • Strong written and verbal communication skills with the ability to collaborate across multidisciplinary engineering teams.
  • Ability to obtain and maintain a Government Public Trust clearance.
  • Experience supporting the Department of Veterans Affairs (VA), Department of Defense (DoD), or other Federal healthcare organizations.
  • Experience developing AI-enabled clinical workflow, information-retrieval, or clinician-support applications requiring human validation.
  • Experience implementing vector search, embeddings, semantic search, and prompt orchestration.
  • Knowledge of Responsible AI, NIST AI Risk Management Framework (AI RMF), NIST SP 800-53, FISMA, and FedRAMP.
  • Familiarity with clinical terminology standards including SNOMED CT, ICD-10, RxNorm, and LOINC.
  • AWS Developer, AWS AI, Machine Learning, or other AWS cloud certifications are highly desirable.
Benefits
  • Medical, Dental, and Vision Insurance
  • 401(k) with Employer Match
  • Paid Time Off plus Federal Holidays
  • Corporate Laptop
  • Professional Development and Training Opportunities
  • Remote Opportunity

Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability, or protected veteran status.

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