QA Engineer- Mobile/AI Application

Charger Logistics Inc. is a world- class asset-based carrier with locations across North America. With over 20 years of experience providing the best logistics solutions, Charger Logistics has transformed into a world-class transport provider and continues to grow.

Charger Logistics invests time and support its employees to provide them with the room to learn and grow their expertise and work their way up. We are entrepreneurial-minded organization that welcomes and support individual ideas and strategies.

We are seeking an experienced Quality Assurance Engineer with expertise in mobile application testing, test automation, and a strong understanding of AI-powered applications. The ideal candidate will ensure the quality, reliability, usability, and performance of Android and iOS applications while contributing to automation initiatives, AI testing strategies, and continuous quality engineering practices.

This role requires collaboration with developers, product managers, designers, DevOps teams, and business stakeholders throughout the software development lifecycle.

Responsibilities

• Design, develop, and execute comprehensive test plans, test cases, and test scenarios for mobile applications, APIs, and backend services.
• Perform manual and automated testing for Android and iOS applications with an automation-first approach.
• Validate functional, regression, smoke, sanity, integration, exploratory, end-to-end, user acceptance, and non-functional testing.
• Execute cross-device and cross-platform testing using real devices, emulators, and cloud-based testing platforms.
• Test REST APIs using Postman, ReadyAPI, Bruno, Rest Assured, or similar tools.
• Validate backend services and databases using SQL and other database technologies.
• Create, maintain, and enhance mobile automation frameworks using Appium, Espresso, XCUITest, Selenium, Cucumber, Tricentis Tosca, or similar tools.
• Validate AI-powered features including AI chatbot functionality, Prompt validation, AI response accuracy and consistency, Hallucination detection, Agentic AI workflow validation.
• Contribute to the analysis of business and technical requirements to ensure comprehensive test coverage.
• Identify, document, prioritize, and track defects using Jira, Azure DevOps, qTest, or similar tools, including detailed reproduction steps and root cause analysis.
• Participate in Agile ceremonies including sprint planning, stand-ups, retrospectives, backlog refinement, and release planning.
• Support shift-left testing practices, in-sprint testing, and continuous quality improvements throughout the SDLC.
• Integrate automated test suites into CI/CD pipelines using Jenkins, GitHub Actions, Azure DevOps, or similar platforms.
• Monitor application quality through logs, analytics, crash reports, and production insights.
• Develop reusable automation utilities, testing frameworks, and quality engineering best practices.
• Collaborate with cross-functional engineering teams to improve product quality, resolve technical challenges, and communicate testing progress and project risks to stakeholders.

Requirements

• 5+ years of software Quality Assurance experience with strong expertise in mobile application testing.
• Hands-on experience testing Android and iOS applications, including native, hybrid, or cross-platform mobile applications.
• Strong experience executing both manual and automated testing.
• Experience with mobile automation frameworks such as Appium, Espresso, XCUITest, Selenium, Cucumber.
• Strong understanding of SDLC, STLC, Agile methodologies, DevOps, shift-left testing, and CI/CD practices.
• Experience with API testing using Postman, ReadyAPI, Bruno, Rest Assured, or similar tools.
• Programming experience in Java, Python, Groovy, C#, or similar languages to support automation development.
• Experience with SQL for database validation and familiarity with databases such as MongoDB, DB2, or IMS.
• Experience with Git, Jenkins, GitHub Actions, Azure DevOps, Jira, Confluence, or qTest.
• Excellent defect reporting, debugging, troubleshooting, and root cause analysis skills.
• Strong analytical, problem-solving, and communication skills with the ability to collaborate effectively across technical and business teams.

Preferred Qualifications

• Experience testing AI/ML-enabled applications.
• Knowledge of Generative AI, Large Language Models (LLMs), and AI-assisted software testing.
• Experience evaluating AI-generated outputs for accuracy, consistency, bias, and safety.
• Experience testing AI chatbots, prompt engineering, or agentic AI workflows.
• Experience using AI tools to generate, optimize, or maintain test cases and automation scripts.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of performance testing tools such as JMeter.
• Experience with Browser Stack, Sauce Labs, or similar cloud-based device testing platforms.
• Continuous learning mindset with the ability to work independently in a fast-paced Agile environment.

Benefits

• Competitive Salary
• Healthcare Benefit Package
• Career Growth