{"id":4077841,"url":"https://alion.io/job/oxiliry-senior-sqa-automation-engineer","title":"Senior SQA Automation Engineer","company":{"id":4523141,"name":"Oxiliry","domain":"oxiliry.com","url":"https://alion.io/company/oxiliry","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Karachi, Pakistan"],"countries":["PK"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":6,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Appium","optional":false},{"name":"C#","optional":false},{"name":"ChatGPT","optional":false},{"name":"CI/CD","optional":false},{"name":"Claude","optional":false},{"name":"Copilot","optional":false},{"name":"Cypress","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Git","optional":false},{"name":"GitHub Actions","optional":false},{"name":"GitLab CI","optional":false},{"name":"Hallucination","optional":false},{"name":"JavaScript","optional":false},{"name":"Jenkins","optional":false},{"name":"LLM","optional":false},{"name":"Playwright","optional":false},{"name":"Postman","optional":false},{"name":"Pytest","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Rest-Assured","optional":false},{"name":"Scrum","optional":false},{"name":"Selenium","optional":false},{"name":"SQL","optional":false},{"name":"TypeScript","optional":false},{"name":"XCUITest","optional":false},{"name":"AWS","optional":true},{"name":"Docker","optional":true},{"name":"JMeter","optional":true},{"name":"k6","optional":true},{"name":"OWASP","optional":true},{"name":"Self-Healing","optional":true}],"status":"live","first_seen_at":"2026-11-11T16:03:22Z","employer_posted_date":"2026-11-11","last_verified_at":"2026-11-11T16:03:22Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Senior SQA Automation Engineer\nDepartment: Software Engineering\nExperience: 6-10 years (minimum 4 in hands-on test automation)\nEmployment Type: Full-Time\nAbout the Role\nReBiz is hiring a hands-on Senior SQA\nAutomation Engineer to build and own scalable test automation across our web,\ndesktop, and mobile applications, APIs, and backend services.\nAI-assisted testing is a core requirement\nof this role, not an add-on. You will use AI tools daily to generate, review,\nand maintain tests, and you will help validate the AI-enabled features in our\nproducts.\nWe are looking for an engineer with\nstrong programming fundamentals, clear ownership, and a track record of\nimproving how quality is engineered.\nKey Responsibilities\n1. Test Automation & Quality Engineering\nDesign, build, and maintain\nscalable automation frameworks for web, desktop, and mobile applications, APIs,\nand backend services.\nAutomate functional, regression,\nintegration, and end-to-end tests, and integrate them into CI/CD pipelines.\nValidate REST APIs, third-party\nintegrations, scheduled jobs, and asynchronous processes.\nTest desktop and mobile\napplications across supported operating systems, devices, and versions, including\ninstallation, upgrade, and offline behavior.\nValidate application behavior\nduring migrations, upgrades, and deployments, and support performance and\nfailure-recovery testing.\nInvestigate complex defects and\nwork with developers on root-cause analysis.\n2. Data & Database Testing\nPerform SQL-based data\nverification, reconciliation, and reporting validation.\nTest database logic, including\nstored procedures, functions, triggers, and views, for correctness, edge cases,\nerror handling, and performance.\nValidate ETL processes and data\npipelines end to end, including source-to-target mapping, transformation logic,\nand data synchronization workflows.\nImplement automated data quality\nchecks for completeness, accuracy, duplicates, null handling, and referential\nintegrity.\nValidate schemas and data\ncontracts to catch breaking changes between services and upstream sources.\nManage test data, including\ngeneration, seeding, and masking or anonymization, so that no real customer\ndata is used in test environments.\nTest system behavior and query\nperformance at realistic data volumes.\n3. AI-Assisted Testing\nUse AI-assisted tools (e.g.,\nGitHub Copilot, Claude, ChatGPT) as part of daily work to generate test cases,\nwrite automation code, and maintain existing suites.\nReview all AI-generated test code\nfor correctness, assertion strength, maintainability, and security before it is\nmerged.\nApply AI to failure analysis,\nflaky-test triage, and regression suite optimization.\nTest AI-enabled product features\nfor output accuracy, consistency, and reliability, including building\nevaluation datasets and prompt-based regression checks.\nEvaluate emerging AI testing tools\nand adopt those that deliver measurable gains.\nFollow responsible-use practices:\nno customer, production, or confidential data is entered into external AI\ntools.\n4. Release Quality & Process\nOwn test planning and test\nstrategy for assigned products, applying risk-based testing to critical\nbusiness workflows.\nDefine and maintain automated\nquality gates in CI/CD that block releases failing agreed criteria.\nDrive release-readiness\nassessments, defect triage, and regression analysis.\nTrack and report quality metrics,\nincluding automation coverage, flaky-test rate, and defect leakage to\nproduction.\nIdentify testing gaps and\nimplement improvements to QA practices.\n5. Collaboration\nWork with Development, DevOps,\nProduct Management, and SQA teams on testability and automation architecture.\nShare automation techniques and\nAI-assisted testing practices with colleagues.\nCommunicate test outcomes, risks,\nand recommendations clearly to stakeholders.\nRequired Skills\nTest Automation & Engineering\nStrong programming skills in at\nleast one of TypeScript/JavaScript, Python, Java, or C#.\nHands-on experience with\nPlaywright, Selenium, or Cypress, including designing and maintaining\nautomation frameworks.\nHands-on experience testing and\nautomating desktop or mobile applications, using tools such as Appium,\nWinAppDriver, FlaUI, Espresso, or XCUITest.\nStrong REST API automation\nexperience using code-based tools such as Playwright API testing, REST Assured,\nPytest, or Postman with Newman.\nStrong SQL skills, including\ntesting stored procedures, functions, and triggers, and validating data across\nrelational databases.\nExperience testing ETL processes\nor data pipelines, including source-to-target validation and automated data\nquality checks.\nExperience with test data\nmanagement, including data generation, seeding, and masking of sensitive data.\nExperience with Git and CI/CD\ntools such as GitHub Actions, GitLab CI, or Jenkins.\nExperience with functional,\nregression, integration, end-to-end, and exploratory testing.\nUnderstanding of Agile/Scrum\npractices and the software development lifecycle.\nStrong debugging, analytical, and\nproblem-solving skills.\nAI Competency (Mandatory)\nDemonstrated hands-on use of\nAI-assisted development tools (e.g., GitHub Copilot, Claude, ChatGPT) in\nproduction test automation work, with examples of measurable impact on\ncoverage, speed, or maintenance effort.\nAbility to critically review\nAI-generated code and identify incorrect logic, weak assertions, brittle\nlocators, and security issues.\nWorking knowledge of prompting\ntechniques for test generation, and of AI tool limitations such as\nhallucination and non-deterministic output.\nPractical experience validating\nLLM-based features or AI-generated outputs, including output validation, prompt\ntesting, and regression datasets.\nUnderstanding of safe AI usage,\nincluding data privacy and confidentiality when using external AI tools.\nPreferred Skills\nExperience with AI-augmented\ntesting platforms, such as self-healing tests or visual AI testing.\nExperience with AWS, Docker, and\nmicroservices-based applications.\nExposure to performance testing\ntools such as JMeter or k6.\nExperience with analytics\nplatforms, BI tools, and reporting systems.\nKnowledge of application security\ntesting and OWASP principles.\nProfessional Competencies\nStrong ownership and\naccountability.\nAnalytical thinking and\nindependent problem-solving.\nEffective collaboration with\ncross-functional engineering teams.\nClear written and verbal\ncommunication.\nAbility to prioritize work across\nmultiple projects.\nWillingness to mentor colleagues\nand share technical knowledge.\nAdaptability to emerging\ntechnologies, particularly AI-driven engineering practices.\nQualifications\nBachelor's degree in Computer\nScience, Software Engineering, or a related field, or equivalent practical\nexperience.\n6-10 years of professional\nexperience in software quality assurance, including at least 4 years building\nand maintaining automation frameworks.\nDemonstrated record of improving\nautomation coverage and testing processes.\nExperience working with\ncross-functional engineering teams on complex software 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