QC Automation Engineer
Aizon
QC Automation Engineer
Aizon
AI-powered optimization of pharma manufacturing
Report to: QC LEAD
Design and own the end-to-end automated test strategy for Aizon products, covering functional, regression, integration, and API test layers across both SaaS platforms based on the guidelines defined by the QC Lead.
Worked closely with Agile development teams and stakeholders to develop and maintain the automation testing framework, using tools such as Jira.
Define and execute manual tests when necessary.
Schedule Testing activities.
Take objective evidence on different devices, browsers, and operating systems.
Report testing results.
Collaborate with developers to define unit and integration tests.
Identify and troubleshoot issues or potential risks in the platform at an early stage of the development cycle.
Work with the Release Engineering team to create and maintain an automated set of “smoke” and regression tests.
Provide assistance to Product Owners while they create business requirements and map them with the test strategy and specifications.
Review requirements, specifications, user documentation, help files, and other project documentation to ensure the quality of the platform and tests to be developed.
Guide testing and compliance efforts to ensure regulatory, quality, and safety priorities are adequately addressed.
Line management and Performance appraisal activities for STEs and SDETs in the Quality Control Team.
Generate structured, human-readable test evidence reports and execution logs that comply with GMP documentation requirements and are ready for internal and customer regulatory audits.
Automate validation of Aizon AI/ML model management workflows, including model deployment, monitoring, and drift-detection test scenarios.
Maintain a comprehensive traceability matrix that links requirements, test cases, and automated evidence artifacts, supporting IQ/OQ/PQ validation packages for customer deliverables.
Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field.
Similar experience (at least 5 years) with automated testing methodologies, tools, and manual testing. Proficient in spoken and written English
Knowledge of programming in Python and/or JavaScript/TypeScript for writing maintainable, scalable automated test code.
Deep knowledge of automated testing methodologies and tools is required
Programming knowledge and experience (JavaScript/Java) is required
End-to-end testing experience is required
Hands-on experience with UI and API test automation frameworks (e.g., Playwright, Selenium, Cypress, Pytest, RestAssured, or equivalent).
Experience integrating automated tests into CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, or equivalent).
Willing to comply with and follow all regulations required when working in a highly regulated environment, such as ISO standards and GMP regulations.
Demonstrated ability to produce human-readable, audit-ready test evidence and traceability documentation suitable for regulated GxP environments.
Develop CI/CD-integrated pipelines (Jenkins, GitHub Actions, or equivalent) that automatically trigger and report test execution on every build, providing continuous quality feedback to the Engineering team.
Experience with automated performance tests
Experience in working with popular testing frameworks (Cypress, Cucumber)
IT cloud tools knowledge is desirable (Amazon Web Services)
Atlassian ecosystem: Confluence, Jira, Bitbucket
Google G Suite
Risk management
Agile software development
Research and evaluate emerging test-automation and AI-assisted testing tools, introducing innovations that increase coverage and reduce execution time.
Knowledge of AI/ML model validation approaches, including testing for model outputs, drift detection, and audit trails in GxP settings.
Familiarity with pharmaceutical manufacturing processes and systems (MES, LIMS, DCS, QMS, ERP) relevant to GMP environments.
Experience with performance and load testing tools (k6, Locust, JMeter, or similar) for SaaS application benchmarking.
Critical eye to stress the platform and to be quality-oriented
Possessing an agile mindset, fast to adapt to constant changes, and feeling comfortable with it
Naturally questioning everything
Excellent communication skills, both within and outside the team
Have experience working on a dynamic product that is ever-changing and evolving rapidly
Commitment to quality
Strong analytical and creative problem-solving skills
Ability to take smart risks and champion new ideas
Team player, collaborative, innovative, get things done mindset
Ability to understand business requirements and translate them into technical requirements
Show initiative in setting and meeting goals within an environment of managed change
Aizon.ai applies artificial intelligence to pharmaceutical manufacturing to improve quality and productivity. Its core offerings are AI-powered predictive solutions and Aizon Consulting Services (ACS), which tailor these solutions to each client. The product works by analyzing a client’s manufacturing data to build predictive models that optimize operations, reduce waste, and ensure compliant, on-time production. Clients see the results through a fast, six-week implementation path and ongoing consulting, demonstrations, and customized deployment. Aizon differentiates itself by serving the highly specialized pharma manufacturing niche with a diverse, multidisciplinary team, a strong emphasis on collaboration and integrity, and a low-risk ROI through rapid, tangible improvements. The company’s goal is to help pharmaceutical manufacturers maximize data value to deliver high-quality drugs on schedule and within budget.
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