Software Development Engineer in Test (SDET)

GDT - General Datatech; Plano (TX); On-site; USD 45,000 - 65,000; Full time

Job summary

GDT - General Datatech in Plano, TX is seeking a hands-on SDET who writes code, builds automation, and uses AI-assisted workflows to improve quality across Android devices, cloud services, APIs, and web apps.

You will collaborate with Product Managers, Developers, Architects, and fellow Quality Engineers to validate new capabilities, expand automation coverage, reduce risk, and raise the overall engineering quality bar.

Qualifications

• Bachelor's degree or equivalent practical experience in CS/Software Eng.
• 3+ years in software development, test automation, or quality engineering.
• Experience validating complex features and end-to-end workflows.
• Familiarity with CI/CD pipelines and Agile environments.
• Strong debugging, troubleshooting, analytical, and communication skills.

Responsibilities

• Design, develop, and maintain automated test frameworks and suites.
• Create automated tests for UI, APIs, backend services, and workflows.
• Use AI-assisted tools to accelerate test design and coverage improvement.
• Integrate testing into CI/CD pipelines and support quality gates.
• Collaborate with Product, Development, and QA teams to improve testability.
• Coach teams on quality practices and automation strategy.

Skills

Debugging

Troubleshooting

Analytical thinking

Communication

Collaboration

Agile

Education

Bachelor's degree in Computer Science or related field

Tools

Playwright

Appium

Selenium

Azure DevOps

Job description

Software Development Engineer in Test (SDET)

Pay rate around $40/hr, depending on experience

The Software Development Engineer in Test (SDET) is an AI-native quality engineer embedded with an engineering team who plays a critical role in assessing risk, assuring quality, improve release confidence, and helping all engineers adopt stronger quality practices. This role combines software engineering, test automation, exploratory testing, risk analysis, release readiness, coaching, and AI-assisted workflows to help teams prevent defects early, validate product behavior, and ship reliable software with confidence. The SDET works closely with Product Managers, Developers, Architects, and fellow Quality Engineers to validate new capabilities, expand automation coverage, reduce risk, improve release confidence, and help raise the overall engineering quality bar across Android devices, cloud services, APIs, integrations, and web applications. The ideal candidate is a hands-on engineer who writes code, builds automation, thinks critically about risk, and uses AI-assisted workflows to improve how quality is built, tested, coached, and released across the team.

Responsibilities

AI-Native Test Automation, Engineering, and Delivery

• Design, develop, and maintain automated test frameworks, test suites, utilities, and tools that improve coverage, testability, and engineering efficiency.
• Create automated tests for user interfaces, APIs, backend services, integrations, and critical end-to-end workflows.
• Use AI-assisted development and testing tools to accelerate test design, automation development, defect investigation, risk analysis, and coverage improvement while applying engineering judgment to ensure accuracy and maintainability.
• Integrate automated testing into CI/CD pipelines, monitor execution, investigate failures, and support quality gates that improve release confidence.
• Participate in code reviews and collaborate with engineering teams to improve application testability, deployment confidence, and release velocity.

Team Quality, Risk Management, and Release Readiness

• Help the team assess quality outcomes by identifying risks, validating product behavior, improving test coverage, and ensuring releases meet customer and operational expectations.
• Plan and execute risk-based testing for complex features, integrations, and end-to-end workflows across Android devices, cloud services, APIs, and restaurant-facing experiences.
• Support release readiness through feature validation, regression testing, deployment verification, post-deployment smoke testing, and production validation.
• Investigate, reproduce, verify, and help troubleshoot defects, including targeted regression and root cause analysis when quality issues occur.
• Partner with Product Managers, Developers, Architects, and fellow Quality Engineers to assess readiness, expose quality risks, improve testability, and provide clear release recommendations.
• Work closely with developers, product managers, architects, and fellow quality engineers.
• Coach and train engineers on quality practices, testability, automation strategy, risk-based testing, and engineering behaviors that improve product quality.
• Participate in Agile ceremonies and cross-functional planning activities.
• Foster a culture where quality is a shared responsibility.
• Help engineering teams adopt quality practices earlier in the development lifecycle so quality is built in rather than inspected at the end.
• Communicate testing progress, risks, and recommendations clearly to stakeholders.

Required Qualifications:

• Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience.
• 3+ years of experience in software development, test automation, or quality engineering.
• Experience validating complex software features and end-to-end business workflows.
• Experience testing APIs, web applications, mobile applications, and distributed systems.
• Familiarity with CI/CD pipelines and DevOps practices.
• Experience working within Agile software development environments.
• Strong debugging, troubleshooting, analytical, and problem-solving skills.
• Excellent communication and collaboration skills.

Preferred Qualifications:

• Experience with Playwright, Appium, Selenium, or similar automation frameworks.
• Experience testing Android applications and devices.
• Experience with Azure DevOps or similar ALM platforms.
• Experience testing cloud-native applications and microservices.
• Experience with exploratory testing and risk-based testing techniques.
• Exposure to performance, reliability, or security testing.
• Experience applying AI-assisted engineering tools in software development workflows