1

Ai Automation Testing Jobs in Washington (NOW HIRING)

Quality Engineer

Bethesda, MD · On-site

$76K - $99K/yr

Perform manual testing of web applications across multiple browsers and platforms. * Understand and ... Maintain and enhance existing automation suites. * Leverage AI-assisted coding tools such as Cursor ...

The ideal candidate possesses strong mortgage industry knowledge, hands-on automation testing ... Leverage modern AI-assisted tools, including Microsoft Copilot, ChatGPT, and Visual Studio Code ...

Showing results 41-60

Ai Automation Testing information

What is AI automation testing?

AI automation testing refers to the use of artificial intelligence technologies to automate the process of testing software applications. This approach enhances traditional automated testing by using machine learning and data analysis to identify test cases, detect defects, and optimize test coverage. AI-driven testing tools can adapt to changes in the application, reduce manual effort, and improve the accuracy and speed of testing processes. As a result, organizations can deliver higher-quality software more efficiently.

What are the key skills and qualifications needed to thrive as an AI automation testing professional?

To thrive as an AI Automation Testing professional, you need a solid understanding of software testing principles, programming languages (such as Python or Java), and AI/ML concepts, often supported by a degree in computer science or a related field. Familiarity with automation tools like Selenium, Appium, and AI-powered testing frameworks, as well as certifications like ISTQB, is highly valued. Strong analytical thinking, attention to detail, and effective communication skills help professionals excel in diagnosing issues and collaborating with development teams. These skills ensure the delivery of robust, efficient, and reliable AI-driven software products in a competitive technology landscape.

What are some common challenges faced by AI automation testing professionals when validating machine learning models?

AI Automation Testing professionals often encounter challenges such as ensuring that test cases comprehensively cover the unique behaviors of machine learning models, dealing with non-deterministic outputs, and handling large datasets efficiently. It's also common to face difficulties in setting up reliable test environments that simulate real-world data scenarios. Collaboration with data scientists and developers is crucial to define meaningful metrics and effectively interpret test results, ensuring the AI system meets both functional and ethical standards.

What is the difference between Ai Automation Testing vs Software Test Engineer?

AspectAi Automation TestingSoftware Test Engineer
Required CredentialsCertifications in AI, automation tools, programming languagesSoftware testing certifications (ISTQB, CSTE), programming skills
Work EnvironmentFocus on automation frameworks, AI integration, scriptingManual and automated testing, test case design, bug tracking
Employer & Industry UsageTech companies, AI-driven projects, software development firmsSoftware development companies, IT departments, QA teams

Ai Automation Testing and Software Test Engineer roles overlap in testing skills and programming knowledge. However, Ai Automation Testing emphasizes AI integration and automation frameworks, while Software Test Engineers focus more on manual testing, test case creation, and bug identification. Both roles are essential in software quality assurance but serve different aspects of the testing process.

How to become an AI automation tester?

To become an AI automation tester, you should have a strong understanding of software testing principles, programming languages such as Python or Java, and experience with automation tools like Selenium or TestComplete. Familiarity with AI and machine learning concepts can be beneficial, along with certifications in testing or automation. Gaining hands-on experience through internships or projects is also valuable for this role.

Is AI automation testing a good career?

AI automation testing is a growing field within software quality assurance that involves using AI tools and scripting to automate test cases, increasing efficiency and coverage. It requires knowledge of programming, testing frameworks, and AI concepts, making it a valuable skill set with strong job prospects and competitive salaries.

What are popular job titles related to Ai Automation Testing jobs in Washington?

For Ai Automation Testing jobs in Washington, the most frequently searched job titles are:

What cities in Washington are hiring for Ai Automation Testing jobs?

Cities in Washington with the most Ai Automation Testing job openings:

Infographic showing various Ai Automation Testing job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 8% Part Time, 2% Temporary, 7% Contract, and 1% Nights. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution.

Senior Quality Assurance Engineer (Automation)

Assurety Consulting Inc

Washington, DC • Remote

$110K - $115K/yr

Full-time

Medical, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Status: Full Time/USA Remote. Experience: 6-8 years Required: Public Trust - Sensitive Level (USA Citizen or Green Card) Benefit: Competitive Pay, Generous PTO and Holiday Schedule, Comprehensive Health Plan, 401(k), and Collaborative Team Atmosphere Salary Range: $110K to $115K Summary: Assurety is an industry leader in the postal and parcel ecosystem, with 21+ years of experience serving government and commercial sectors, including postal/parcel, marketing, finance, retail, and higher education. We leverage data and technology to solve complex problems, fostering a culture of collaboration, innovation, and ownership.

Our solutions help clients save lives, cut costs, boost revenue, strengthen the U.S. economy, and enhance customer experiences. This QA Automation Engineer - Level 3 role is a senior-level position focused on leading automation efforts, enhancing QA frameworks, and ensuring high-quality delivery across USPS enterprise systems

This role is ideal for a QA professional with strong technical depth, leadership experience, and expertise in both manual and automation testing across complex enterprise applications, including Payroll systems. You'll work closely with cross-functional teams to align QA practices with business goals, ensure compliance with USPS standards, and drive continuous improvement across platforms. Key Responsibilities Lead QA automation efforts across multiple USPS systems, including functional, integration, transactional, API, regression, smoke, and end-to-end (E2E) testing.

Design, implement, and maintain scalable automation frameworks and test scripts that support enterprise-level testing needs. Collaborate with product owners, developers, business analysts, PMO, and other stakeholders to ensure comprehensive test coverage and alignment with business and technical requirements. Develop and review test strategies, test plans, test data, and testing procedures to validate complex business workflows and system integrations.

Mentor junior QA engineers and contribute to team development through technical guidance and knowledge sharing. Oversee the planning and execution of automated and manual testing activities, ensuring timely, high-quality releases and compliance with USPS Technology Solution Life Cycle (TSLC) standards. Conduct advanced testing, including performance, security, integration, and functional validation of enterprise applications.

Analyze test results, verify defect resolutions, identify testing risks, and communicate recommendations and mitigation strategies to stakeholders and leadership. Contribute to system architecture discussions to improve testability, automation coverage, and long-term maintainability. Support post-deployment validation and production monitoring to ensure sustained software quality.

Participate in strategic QA planning, Agile ceremonies, and continuous process improvement initiatives, leveraging AI-assisted testing tools where appropriate to improve testing efficiency. Qualifications Required 6-8 years of experience in Software Quality Assurance, with a strong focus on automation and enterprise systems. Proven experience leading QA efforts and managing manual and automated testing initiatives across multiple platforms.

Expertise in automation tools, frameworks, and scripting for API, functional, integration, and data-driven testing. Deep understanding of SDLC, software testing methodologies, Agile/Scrum practices, and CI/CD or DevSecOps environments. Strong proficiency in SQL, Excel (Pivot Tables), PowerPoint, and reporting tools.

Experience developing test plans, test scripts, test data, and validating complex business workflows. Excellent analytical, problem-solving, communication, and stakeholder management skills. Bachelor's degree in Computer Science, Engineering, or a related technical field.

Preferred Experience with Payroll, HRIS, Finance, or other enterprise transactional systems, including payroll processing, taxes, deductions, benefits, and payroll lifecycle workflows. Experience using AI-assisted testing or AI-generated test scripting tools to improve testing efficiency. Certifications in QA, Automation, or Cloud platforms (e.g., ISTQB, AWS, Azure)

Experience with performance and security testing tools. Familiarity with USPS systems, regulatory compliance, enterprise risk management, and VersionOne or equivalent Agile management tools. Background in business-to-business transactional systems, workflow automation, enterprise architecture, and product lifecycle decisions.

Mainframe testing experience is considered an advantage. What Success Looks Like in This Role Automation frameworks are reliable, reusable, and aligned with USPS enterprise standards. QA deliverables are consistently high-quality, timely, and aligned with business needs.

Risks are proactively identified and mitigated through strong testing and collaboration. QA processes are well-documented, standardized, and continuously improved. Stakeholders view QA as a key contributor to successful product delivery and operational excellence.