QA Tech Lead

• Lead and mentor automation engineers and provide technical guidance to the wider testing team
• Support team skill development, including cross-training manual testers in automation and AI-assisted scripting
• Collaborate with Development, Customer Success, Product Management, Design, and Product Support across multiple time zones
• Define the risk-based test strategy and criteria for automated, manual, and unnecessary tests
• Own automation test plans and standards across all product releases
• Create and maintain quality metrics, KPIs, and testing dashboards; report updates to the Director of Engineering
• Define test scope, objectives, success criteria, and resource estimates with stakeholders
• Identify, assess, and mitigate quality risks throughout sprint cycles and pre-release dry runs
• Architect, build, and maintain scalable automation frameworks, including the custom Playwright framework
• Develop and execute automated system, integration, regression, and API tests
• Serve as technical point of contact and subject matter expert on code and system architecture
• Identify manual test cases for automation and prioritize their transition with the Test Lead
• Move automated suites to tiered CI/CD quality gates in GitHub Actions, including Smoke, Sanity, and Nightly Regression suites
• Maintain test suite health by resolving flaky tests and tracking automation coverage
• Oversee Playwright and Zephyr Scale integration using automated JUnit XML reporting pipelines
• Oversee test environments and test data management
• Perform manual testing where automation is impractical, defect triage and resolution, and UAT
• Contribute automation coverage and results to validation documentation, including Test Plans, Test Summary Reports, Traceability Matrices, and UAT Scripts

• Bachelor's degree in Computer Science, Engineering, or related field
• Minimum 7 years of experience in software testing or QA engineering, including at least 2 years in a technical or automation lead role
• Hands-on experience testing large-scale enterprise SaaS web applications and complex software systems, including RBAC, multi-tenant data isolation, and API integration layers
• Experience leading automation engineers and working closely with manual testers
• Solid understanding of manual testing, including boundary value analysis, equivalence partitioning, exploratory testing, and regression planning
• Ability to assess automation ROI and recommend the balance of manual and automated testing based on risk, release cadence, and product maturity
• Expert-level proficiency in Playwright (TypeScript/JavaScript or Python), including building frameworks from the ground up using POM
• Experience with other automation tools such as Selenium and REST Assured
• Strong hands-on programming skills in TypeScript, Python, and JavaScript
• Working knowledge of database technologies
• Proficiency in performance testing tools such as JMeter and LoadRunner
• Experience with CI/CD pipelines, DevOps practices, and test integration strategies
• Expertise in the SDLC and test management tools such as Jira and Zephyr Scale
• Hands-on experience automating test execution uploads to Zephyr Scale via APIs
• Strong verbal and written communication skills, with the ability to explain technical topics to non-technical team members
• Ability to balance long-term automation architecture with immediate release needs
• Team leadership skills, including delegating and prioritizing work, giving constructive feedback, and supporting team member growth
• Commitment to staying current with industry trends and emerging testing technologies
• Experience working in fast-paced, innovative technology environments
• Experience in collaborative, agile teams that regularly deploy high-quality software to production
• Strong business acumen and understanding of quality's impact on customer success and business outcomes
• Experience testing in regulated environments such as GxP, computer system validation, or 21 CFR Part 11
• Experience testing AI/LLM-powered features and validating non-deterministic outputs
• Experience configuring AI coding assistants such as Claude for QA scripting workflows
• Background in lightweight DevOps tasks, such as Docker and managing staging/test environments

• Mentorship from AI and business strategy experts
• Clear career progression
• Exposure to LLMs and conversational AI
• Competitive pay and benefits
• Results-driven, innovative culture