Client: Our client is a global organization focused on professional education and certification.

- Project overview: Our client, a globally recognized leader in investment management education and certification, operates a scaled Quality Engineering function across a broad technology landscape — SaaS and custom-built systems spanning ERP, CRM, CMS, LMS, e-commerce, exam and certification delivery, and supporting data platforms running across AWS and Azure. With an AI-native testing platform, automation-first practices, and a structured weekly release cadence, the client treats quality as a continuous team responsibility rather than a final-gate checkpoint.
- QE Leads own day-to-day quality for an assigned delivery team and contribute to a shared Playwright + TypeScript automation platform already in production across all teams. Leads join an established platform and operating model rather than build tooling from scratch.

- Position overview: We are looking for an experienced Quality Engineering Lead with strong hands-on command of the full testing lifecycle and practical depth in Playwright and TypeScript. You lead people and process while remaining hands-on in an automation-first environment — guiding your team to build automated coverage within the sprint using AI-assisted workflows, and taking direct ownership of story analysis, test planning, test design, automation, defect management, and release readiness.
- In this role you are the quality anchor for a focused delivery team — close enough to the work to guide engineers, review coverage, and keep automation healthy, while also carrying the judgment needed to confirm release readiness and communicate quality status confidently to senior QE leadership. You will operate within an established QE structure, collaborating daily with your team and aligning on risks, release status, and continuous improvement.
- This position is intended for Hyderabad-based candidates who are available to work from the office.

Technology stack: TypeScript, Playwright, test case management platforms (TestRail or equivalent), test reporting platforms (Allure or equivalent), AI-assisted QE tooling across the full lifecycle (Cursor, GitHub Copilot, or equivalent), CI/CD pipelines, Git, defect tracking systems, team coordination tools (Jira, sprint boards), cloud-based test environments

- Responsibilities:



Own quality end to end for the assigned delivery team — from story analysis and test design through in-sprint automation delivery to release readiness.
- Analyze stories, acceptance criteria, and specifications using AI-assisted tooling to identify test scenarios, coverage gaps, and risks before and during development.
- Define the test plan for each sprint and release — scope, approach, risk-based priorities, and entry/exit criteria — and ensure the team executes against it.
- Design and oversee test cases with AI-assisted support, aligned with sprint deliverables and release scope; review team contributions for coverage quality and consistency.
- Lead the team's in-sprint automation delivery — overseeing and contributing to UI and API test coverage in TypeScript and Playwright using AI-assisted workflows for test design, code authoring, and suite maintenance; direct targeted exploratory and risk-based testing where judgment adds coverage that automated checks alone cannot provide.
- Ensure defects are reported, triaged, tracked, and verified through resolution, coordinating with developers and product on priority and impact.
- Keep test case management and automation results in sync so automated coverage reflects test design and results accurately represent CI state.
- Confirm release readiness for the team's deliverables and provide quality sign-off to senior QE leadership as part of the release process.
- Monitor automation health and defect trends using AI-powered analysis and raise quality concerns proactively.
- Lead, mentor, and develop 2–4 QE Engineers assigned to the delivery team, building capability through coaching, code and test-case review, and deliberate delegation.
- Plan QE capacity and coverage for the team's sprint and release commitments; escalate resource or skill gaps to the QE Domain Lead.
- Represent QE in sprint planning, estimation, daily coordination, and delivery forums for the assigned team.
- Drive active adoption of AI-assisted testing tools and practices within the team.
- Promote quality ownership, testing best practices, and a collaborative high-performing team setting.
- Align team quality goals with Domain Lead direction and program delivery priorities.





- Requirements: Proven experience covering the full testing lifecycle: requirements analysis, test planning, test design, defect management, and test automation — with evidence of ownership at team or lead level.
- Experience defining test plans for sprints and releases, including scope, approach, risk-based priorities, and entry/exit criteria.
- Demonstrated progression from QE Engineer (or equivalent) into a senior QE / lead role with both hands-on delivery and people or mentoring responsibility.
- Experience leading or coordinating QE / QA engineers on a delivery team (capacity, coverage, mentoring, and stakeholder representation).
- Proficiency in TypeScript and hands-on experience with Playwright for UI and API test automation, including ability to write code independently and explain technical decisions.
- Experience with test case management platforms (TestRail or equivalent).
- Familiarity with test reporting platforms (Allure or equivalent) and using results for release readiness decisions.
- Experience working in an AI-assisted development environment (Cursor, GitHub Copilot, or equivalent).
- Understanding of AI agent concepts and their practical application across the testing lifecycle.
- Experience working within CI/CD pipelines, version control (Git), and defining or applying quality gates in delivery pipelines.
- Experience in Agile delivery (Scrum or equivalent) as a QE lead or senior QE collaborating closely with development and product.
- Comfortable working within a multi-tier QE structure, aligning with senior QE leadership on quality status, risks, and escalations.
- Strong analytical, communication, and stakeholder-management skills — able to translate technical quality topics for delivery partners and raise risks clearly.

- Nice to have: Familiarity with cloud-based cross-browser testing platforms (LambdaTest or equivalent).
- Familiarity with cloud secrets management and infrastructure access (AWS Secrets Manager or equivalent).
- Exposure to enterprise SaaS platforms such as ERP, CRM, CMS, or LMS systems in a QE context.
- Experience with API testing tools (Postman or equivalent).
- Familiarity with performance, accessibility, or security testing approaches as a supplement to functional quality gates.
- Exposure to DevOps practices and pipeline optimization.
- Understanding of modern software architecture patterns (microservices, REST, GraphQL).

📌 Principal QE Architect (Hyderabad-based) (Bengaluru)
🏢 DataArt
📍 Bengaluru