[Hiring] Quality Assurance Engineer @Revenue Management Solutions LLC

Role Description

The Quality Assurance (QA) Engineer plays a pivotal role in ensuring the quality, reliability, and performance of our web applications and AI-driven solutions. This role is responsible for designing, building, and maintaining automated test frameworks, conducting hands-on exploratory and UI/API testing, and validating non-deterministic outputs from machine learning models.

In addition to traditional QA practices, you will leverage modern containerization tools (such as Docker) to manage isolated test environments and utilize AI-assisted tools (such as Copilot, synthetic test data generators, and intelligent test execution platforms) to optimize testing workflows, improve test coverage, and accelerate release cycles.

Qualifications

• Hands-on experience with modern web automation and end-to-end testing tools (e.g., Playwright, Cypress, Selenium, or WebdriverIO).
• Solid practical knowledge of Docker (writing Dockerfiles, using Docker Compose) for spinning up containerized applications, databases, and automated testing nodes.
• Proficiency in API testing and automation using tools like Postman, REST Assured, or HTTP clients.
• Solid understanding of modern web architectures (HTML5, CSS3, JavaScript/TypeScript, DOM manipulation, asynchronous state management).
• Strong coding skills in at least one modern language (e.g., TypeScript/JavaScript, Python, C#, or Java).
• Proficiency with SQL (PostgreSQL, SQL Server, MySQL) and experience querying relational or document databases for test setup and verification.
• Familiarity with concepts around evaluating AI/ML features, RAG architectures, prompt engineering testing, or heuristic evaluation metrics.
• Familiarity or experience using AI tools (e.g., GitHub Copilot, ChatGPT, Claude) to write test scripts, create mock data, or generate test scenarios.
• Proven experience working in an Agile/Scrum environment.
• Exceptional analytical, critical thinking, and debugging skills with high attention to detail.
• Excellent written and verbal communication skills to articulate technical defects, risk assessments, and test coverage clearly to technical and non-technical stakeholders.

Requirements

• Design, develop, and maintain robust, scalable automation frameworks for modern single-page web applications (React, Angular, Vue) and microservices/REST APIs.
• Integrate automated test suites into CI/CD deployment pipelines (e.g., GitHub Actions, Azure DevOps, Jenkins) for continuous validation.
• Spin up, manage, and tear down local and cloud-based test environments using Docker containers and container orchestration tools.
• Execute automated test suites inside containerized environments to ensure consistency across local, staging, and production-like setups.
• Develop test strategies to validate AI/ML features, large language model (LLM) outputs, and non-deterministic application behavior for accuracy, relevancy, latency, and edge cases.
• Monitor and measure AI output consistency, safety/bias guardrails, and system performance under varying prompt payloads.
• Utilize AI-assisted development tools and intelligent QA platforms to generate test cases, synthesize realistic test data sets, and accelerate root-cause failure analysis.
• Collaborate closely with Product Owners, Software Engineers, and Data/ML Engineers during Agile/Scrum sprints to refine requirements, acceptance criteria, and edge-case scenarios.
• Participate in code reviews for test automation scripts to ensure high code quality and maintainability.
• Identify, document, prioritize, and track defects using modern issue-tracking tools (e.g., Jira).
• Perform exploratory, regression, performance, and cross-browser/device testing across staging and production environments.
• Assist in setting QA standards, test metrics, and best practices across the engineering organization.

Company Description