QA Engineer – AI

Public Partnerships | PPL

QA Engineer focusing on writing and executing automated tests with a drive for AI-driven quality engineering. Collaborating on system defects and managing test frameworks for various applications.

Posted 7/28/2026full-timeRemote • 🇺🇸 United StatesJunior💰 $75,000 - $80,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Proficient in Business-Driven Development (BDD) testing methodologies and automated testing frameworks, with a strong focus on AI-driven workflows and continuous integration/deployment practices. Demonstrates strong analytical and problem-solving skills, alongside the ability to adapt to new technologies and work independently.

Highest-signal resume keywords

BDD Testing MethodologiesCucumberAutomated Testing FrameworksAI Tools for TestingContinuous Integration/Continuous Deployment

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Automated TestingAPI TestingUI TestingMobile TestingJavaPythonNode.jsSQLTest Case DevelopmentDebugging

Soft Skills

Analytical SkillsProblem-SolvingCommunicationDocumentationSelf-Starter

Tools & Technologies

AI ToolsTesting ToolsCI/CD PipelinesAutomation ScriptsWeb Applications

Industry Keywords

AI AgentsWorkflow ExecutionResponse AccuracyFailure ScenariosData Validation

Tech Stack

Tools & technologies

JavaJavaScriptNode.jsPythonSQL

About the role

Key responsibilities & impact

An AI focused QA Engineer writes, maintains and executes automated tests using Business-Driven Development (BDD) testing methodology for API, UI, mobile, and backend/data validations.
The QA Engineer also collaborates with others to define feature specification, and review resolution to system defects.
Design, develop, and maintain automated test frameworks for web applications, APIs, and AI-driven workflows using modern testing tools and AI-assisted automation.
Utilize AI tools to generate, optimize, and maintain test cases, test scenarios, and automation scripts, improving testing efficiency and coverage.
Design, execute, and validate testing for AI agents, evaluating agent behavior, workflow execution, response accuracy, and failure scenarios.
Support Continuous Integration and Continuous Deployment (CI/CD) pipelines by integrating automated testing into the software development lifecycle.
Demonstrate a self-starter mindset with the ability to quickly learn new technologies, adapt to changing priorities, and work independently.

Requirements

What you’ll need

A quick learner and self-starter who can work independently and adapt to new technologies.
Experience with BDD testing methodologies using Cucumber, along with proficiency in a programming language such as Java, Python, or Node.js.
Experience using AI to generate, improve, and maintain test cases, test scenarios, and automation scripts.
Experience designing, testing, and validating AI agents, including evaluating agent behavior, workflows, responses, accuracy, and failure scenarios.
Ability to use AI tools to develop and enhance automated testing frameworks for applications, APIs, and agent-based workflows.
Strong analytical, problem-solving, communication, and documentation skills.
Strong debugging skills and solid SQL knowledge for data analysis, issue investigation, and validation.
Experience with continuous integration and continuous deployment pipelines.

Benefits

Comp & perks

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