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Ai Automation Testing Jobs in Texas (NOW HIRING)

Lorven Technologies

QA Testing Director

Austin, TX · On-site

$140K - $160K/yr

Secondary Skills / Good to have - Hands on experience in developing utilities using AI; Karate Framework for API testing and Mobile test Automation Job / Role Description * Lead and manage the end-to ...

OmniForce

AI Business Lead

Houston, TX

Promote responsible AI and automation practices, including data governance, approved connector usage, access controls, documentation standards, testing, monitoring, and production support ...

Vertiv

Software Engineer -Automation

Austin, TX · On-site

They are seeking a Systems Software Engineer - Validation Automation & AI to develop scalable ... testing • Evaluate and deploy AI agents capable of generating test cases, creating validation ...

ForeScout

Manager, QA Automation

Dallas, TX · Hybrid

AI & Automation Innovation (what sets this role apart) * Practical interest or experience applying LLMs and generative AI to software testing - prompt engineering for test generation and evaluating ...

Vizient

Senior Analyst, Intelligent Automation

Irving, TX · On-site

$102K - $179K/yr

... AI Builder, UiPath Studio, UiPath Orchestrator, and related technologies Support automation and ... testing, deployment, support, and continuous improvement Ensure automation solutions align with ...

Tata Consultancy Services

Gen AI Engineer

Austin, TX · On-site

The role involves developing AI-driven automation solutions, integrating with LLMs, and ... testing tools • Prioritizing, scheduling, and communicating the status of your work • Diving ...

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Ai Automation Testing information

What are some common challenges faced by AI automation testing professionals when validating machine learning models?

AI Automation Testing professionals often encounter challenges such as ensuring that test cases comprehensively cover the unique behaviors of machine learning models, dealing with non-deterministic outputs, and handling large datasets efficiently. It's also common to face difficulties in setting up reliable test environments that simulate real-world data scenarios. Collaboration with data scientists and developers is crucial to define meaningful metrics and effectively interpret test results, ensuring the AI system meets both functional and ethical standards.

What is AI automation testing?

AI automation testing refers to the use of artificial intelligence technologies to automate the process of testing software applications. This approach enhances traditional automated testing by using machine learning and data analysis to identify test cases, detect defects, and optimize test coverage. AI-driven testing tools can adapt to changes in the application, reduce manual effort, and improve the accuracy and speed of testing processes. As a result, organizations can deliver higher-quality software more efficiently.

What are the key skills and qualifications needed to thrive as an AI automation testing professional?

To thrive as an AI Automation Testing professional, you need a solid understanding of software testing principles, programming languages (such as Python or Java), and AI/ML concepts, often supported by a degree in computer science or a related field. Familiarity with automation tools like Selenium, Appium, and AI-powered testing frameworks, as well as certifications like ISTQB, is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help professionals excel in diagnosing issues and collaborating with development teams. These skills ensure the delivery of robust, efficient, and reliable AI-driven software products in a competitive technology landscape.

What is the difference between Ai Automation Testing vs Software Test Engineer?

AspectAi Automation TestingSoftware Test Engineer
Required CredentialsCertifications in AI, automation tools, programming languagesSoftware testing certifications (ISTQB, CSTE), programming skills
Work EnvironmentFocus on automation frameworks, AI integration, scriptingManual and automated testing, test case design, bug tracking
Employer & Industry UsageTech companies, AI-driven projects, software development firmsSoftware development companies, IT departments, QA teams

Ai Automation Testing and Software Test Engineer roles overlap in testing skills and programming knowledge. However, Ai Automation Testing emphasizes AI integration and automation frameworks, while Software Test Engineers focus more on manual testing, test case creation, and bug identification. Both roles are essential in software quality assurance but serve different aspects of the testing process.

What are popular job titles related to Ai Automation Testing jobs in Texas? For Ai Automation Testing jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Ai Automation Testing jobs in Texas look for? The top searched job categories for Ai Automation Testing jobs in Texas are:
What cities in Texas are hiring for Ai Automation Testing jobs? Cities in Texas with the most Ai Automation Testing job openings:
Ai Automation Testing jobs near you
Infographic showing various Ai Automation Testing job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 9% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

AI Tester - Senior QA Automation Engineer (Selenium & AI Testing)

MDAEdge

Dallas, TX • On-site

Full-time

Re-posted 24 days ago

Job description

Job Summary:
MDAEdge is seeking a highly skilled Senior QA Automation Engineer with extensive experience in Software Functional Testing and Selenium. The ideal candidate will lead system integration testing, ensure adherence to quality standards, and develop AI-specific automated testing frameworks.
Responsibilities:
• Conduct system integration testing for new and enhanced applications.
• Develop and execute automated tests using Selenium and other industry-standard tools.
• Collaborate with project teams to establish plans, standards, and procedures that optimize testing efforts.
• Ensure on-time delivery by monitoring dependencies, progress, and milestones.
• Educate business and development teams on the testing methodology, with a focus on end-to-end quality assurance.
• Lead project and quality management initiatives, including issue tracking and communication.
• Optimize resource utilization by assisting the Testing Manager in reviewing forecasting reports.
• Ensure compliance with Agile methodologies, maintaining detailed process documentation.
• Perform AI-specific testing, including validation of LLMs and RAG architectures using vector databases.
• Implement automated testing frameworks for Gen AI applications, such as DeepEval and RAGAs.
• Develop custom validation scripts for evaluating AI model accuracy, relevance, and faithfulness.
• Test prompt engineering techniques to refine AI-generated responses.
• Execute SQL queries in Snowflake to validate database integrity and application responses.
Qualifications:
Required:
• 6+ years of experience in Software Functional Testing
• 4–7 years of expertise in Selenium
• Expertise in Agile methodologies
• Experience with test automation tools
• Experience in AI model evaluation using LLMs and RAG architectures
• Conduct system integration testing for new and enhanced applications
• Develop and execute automated tests using Selenium and other industry-standard tools
• Collaborate with project teams to establish plans, standards, and procedures that optimize testing efforts
• Ensure on-time delivery by monitoring dependencies, progress, and milestones
• Educate business and development teams on the testing methodology, with a focus on end-to-end quality assurance
• Lead project and quality management initiatives, including issue tracking and communication
• Optimize resource utilization by assisting the Testing Manager in reviewing forecasting reports
• Ensure compliance with Agile methodologies, maintaining detailed process documentation
• Perform AI-specific testing, including validation of LLMs and RAG architectures using vector databases
• Implement automated testing frameworks for Gen AI applications, such as DeepEval and RAGAs
• Develop custom validation scripts for evaluating AI model accuracy, relevance, and faithfulness
• Test prompt engineering techniques to refine AI-generated responses
• Execute SQL queries in Snowflake to validate database integrity and application responses
• Experience with Jira and ALM for test and issue tracking
• Strong proficiency in Python, with experience in AI testing frameworks such as LangChain, Pytest, and PyTorch
• Hands-on expertise in LLM & RAG architecture testing using vector databases
• Familiarity with Snowflake, SQL querying, and data validation techniques
• Excellent communication and leadership skills to engage with stakeholders
Company:
The world doesn't have a talent shortage. It has a talent alignment problem. MDA Edge exists to fix that. Founded in , the company is headquartered in Sheridan, WY, US, , with a team of 51-200 employees. The company is currently Growth Stage.

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