Lead QA Automation Engineer

RJT Compuquest, Inc.
Tampa, FL, United States
3 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Compensation
$93,600.0 - $104,000.0
Working hours
Regular working hours

Tech stack

Multitier Architecture Artificial Intelligence Automation of Tests Client Server Models Code Coverage Software Debugging White-Box Testing Revision Control Systems Load Testing Mainframes Systems Development Life Cycle Regression Testing
+11 more
Requirements Traceability Service-Oriented Architecture Software Engineering Systems Integration Test Data Web Applications Scripting Performance Testing Prompt Engineering Model Validation Api Management

Requirements

Automation Engineering, Test Automation, Test Automation, Automation Engineering, Test Plan/Schedule, Traceability, Performance Testing, Software Development Lifecycle (SDLC), System Integration (SI), Acceptance Testing, Acting as the lead, help create testing and automation solutions for the platform interfacing between POD and other stakeholders.

  • 6+ years hands-on experience defining the testing and automation strategy for large scale programs and ensuring requirements traceability throughout the system development lifecycle. Experience should include leading the testing efforts, including experience with all phases of testing: system integration, user acceptance, and performance testing.
  • 6+ experience driving the quality assurance processes.
  • Prior experience leading teams - onshore, offshore and nearshore.
  • Experience working in a testing role in different environments including the following: client server, service-oriented architecture, web-based, mainframe-based and three-tier architectures.
  • Prior experience with open source automation tools, source control systems, scripting languages, automated reporting, API testing.
  • Experience applying prompt engineering techniques to generate, refine, or debug automated test scripts and test data. A strong understanding of the various approaches used in testing techniques - white-box, black-box, load testing, coverage testing and regression testing.

  • Exposure to AI-assisted defect triage or root-cause analysis tools that reduce manual investigation time.
  • Understanding of responsible AI/testing governance principles (bias detection, explainability, model validation) as applied to QE. Experience contributing to or influencing AI-adoption roadmaps within a testing/QE organization.

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