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Quality Assurance Engineer; Remote

Remote / Online - Candidates ideally in
Oklahoma City, Oklahoma County, Oklahoma, 73116, USA
Listing for: Thompson Street Capital Partners
Remote/Work from Home position
Listed on 2026-10-13
Job specializations:
  • Software Development
    AI QA / Validation Engineer, Software Testing
Salary/Wage Range or Industry Benchmark: 90000 - 120000 USD Yearly USD 90000.00 120000.00 YEAR
Job Description & How to Apply Below
Job 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.

Duties and Responsibilities
  • Modern Web & API Automation:
  • 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., Git Hub Actions, Azure Dev Ops, Jenkins) for continuous validation.
  • Containerized Test Environments & Infrastructure:
  • 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.
  • AI & Model Output Testing:
  • 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.
  • AI-Driven QA Optimization:
  • Utilize AI-assisted development tools and intelligent QA platforms to generate test cases, synthesize realistic test data sets, and accelerate root-cause failure analysis.
  • Cross-Functional Collaboration:
  • 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.
  • Quality Process & Defect Management:
  • 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.
Qualifications

Core Technical Requirements

  • Automation Frameworks: Hands-on experience with modern web automation and end-to-end testing tools (e.g., Playwright, Cypress, Selenium, or WebdriverIO).
  • Containerization & Dev Ops: Solid practical knowledge of Docker (writing Dockerfiles, using Docker Compose) for spinning up containerized applications, databases, and automated testing nodes.
  • API Testing: Proficiency in API testing and automation using tools like Postman, REST Assured, or HTTP clients.
  • Modern Web Technologies: Solid understanding of modern web architectures (HTML5, CSS3, JavaScript/Type Script, DOM manipulation, asynchronous state management).
  • Programming & Scripting: Strong coding skills in at least one modern language (e.g., Type Script/JavaScript, Python, C#, or Java).
  • Database Querying: Proficiency with SQL (PostgreSQL, SQL Server, MySQL) and experience querying relational or document databases for test setup and verification.
AI & Emerging Tech Capabilities
  • AI Feature Testing: Familiarity with concepts around evaluating AI/ML features, RAG architectures, prompt engineering testing, or heuristic evaluation metrics.
  • AI Productivity Tools: Familiarity or experience using AI tools (e.g., Git Hub Copilot, ChatGPT, Claude) to write test scripts, create mock data, or generate test scenarios
Professional & Interpersonal Skills
  • Agile Methodology: Proven experience working in an Agile/Scrum environment.
  • Problem-Solving: Exceptional analytical, critical thinking, and debugging skills with high attention to detail.
  • Communication: Excellent written and verbal communication skills to articulate technical defects, risk assessments, and test coverage clearly to technical and non-technical stakeholders.
Education/Experience

A bachelor's degree is not required, but preferred. More than anything, RMS is looking for people who are passionate about technology who want to develop the skills…

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