Senior QA Engineer – Cloud, AI & Hardware Validation

OpenEye

Liberty Lake (WA)

On-site

USD 34,000 - 41,000

Full time

5 days ago

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Benefits offered by this job

Annual discretionary bonus

Stock purchase program

401k match

Paid maternity/paternity leave

Paid vacation 15 days per year

Paid holidays 9 per year

Educational assistance program

Medical, dental, vision benefits

Job summary

OpenEye is seeking a Senior Software QA Specialist to lead quality efforts across cloud, AI analytics, and hardware-integrated solutions. You will mentor QA staff, shape testing strategies, and drive end-to-end validation from requirements to release readiness.

The ideal candidate brings deep testing expertise, systems knowledge, and strong leadership. You will collaborate with product, engineering, and support to ensure product quality and customer success while growing automation capabilities.

Qualifications

8+ years of software quality assurance or testing in Agile environments.
Strong testing methodologies, risk-based testing and defect management.
Experience leading testing for complex software, cloud, firmware, or hardware.
Ability to drive test strategy and end-to-end validation.
Hands-on API testing using Postman, Swagger or similar tools.
SQL knowledge and database validation experience.
Experience with logging analysis, troubleshooting, and automation.
Familiarity with AI-assisted testing tools and modern QA practices.
Proficiency with Jira, TestRail, Azure DevOps for defect management.
Understanding of web apps, cloud platforms, client/server architectures.

Responsibilities

Lead quality efforts for complex features, releases, and cross-functional initiatives.
Define validation strategies and risk-based testing with product teams.
Develop and execute test plans, test cases, and regression suites.
Validate APIs, systems, and customer workflows across software and hardware.
Coordinate validation activities across workstreams to ensure release readiness.
Investigate defects, reproduce issues, and perform root-cause analysis.
Execute automated test suites; mentor SETs and expand automation.
Analyze automated results, identify risks, and drive corrective actions.
Use AI-assisted testing tools and modern QA practices to improve coverage.
Participate in sprint planning, reviews, and quality sign-off activities.