QE Domain Lead, Hyderabad-based

Location: Bengaluru, India We are seeking a highly experienced QE Domain Lead with a strong background in QA leadership and demonstrated success progressing from a QE Lead role into a QE Manager role. This client facing position requires a holistic and business oriented approach to QA, strong stakeholder management across delivery, product, and engineering, and a practical mindset for embedding AI assisted testing practices into day to day quality engineering. You will be the primary QE contact for an assigned domain, collaborating closely with the client's QE Director and Senior QE Manager, and owning release readiness and quality sign off across all domain releases. The role carries a dual scope, domain level coordination layered on top of team lead responsibilities, managed through deliberate delegation. This role offers direct influence over quality outcomes across a technology domain, a close partnership with senior client leadership, and the opportunity to shape how AI assisted testing practices are adopted at scale. This position is intended for Hyderabad based candidates who are available to work from the office. Our client, a globally recognized leader in investment management education and certification, operates a scaled Quality Engineering function across multiple technology domains. With an AI native testing platform, automation first practices, and a structured weekly release cadence, the client is embedding quality as a continuous practice, not a final checkpoint. The QE Domain Lead sits at the center of this model, connecting project level execution to organizational quality strategy and ensuring that status, risks, and resource needs are visible before they become issues. Serve as the primary QE contact for the domain across delivery, product, and engineering. Own release readiness and quality sign-off for all domain releases, including coordinating multi-team verification across staging and production environments. Coordinate with QE Leads and Senior QEs to stay aligned on active work, risks, and dependencies. Ensure adequate QE coverage and skill sets across projects in the domain. Define risk-based testing approaches and quality gates across multiple concurrent domain projects. Own domain-level quality metrics and drive improvement when targets are not met. Provide regular domain status reporting and represent the domain in QE leadership forums. Estimate QE capacity needs for new projects and initiatives in the domain. Coordinate cross-domain impact assessments when work spans multiple domains. Proactively identify and escalate resource gaps, timeline risks, and quality issues. Represent QE in delivery and product forums within the domain. Collaborate with the domain delivery lead to ensure QE and delivery remain aligned. Drive active adoption of AI-assisted testing tools and practices within the domain team. Mentor QE Leads and Senior QEs, building team capability through deliberate delegation. Proven career progression from QE Lead to QE Manager. Extensive experience in enterprise environments with complex, cross-team delivery structures. Experience engaging delivery, product, and engineering stakeholders in a business context. Excellent communication skills, capable of translating technical topics into business language. Solid understanding of modern QA practices, automation, and AI trends in testing. Working knowledge of Playwright and TypeScript, sufficient to assess automation coverage quality, evaluate automation health, and support informed resourcing decisions. Experience working within CI/CD delivery pipelines, applying Agile practices (Scrum, SAFe, or equivalent), and defining risk-based testing approaches across concurrent projects. Proven experience owning quality metrics, status reporting, and improvement planning across multiple teams. Experience coordinating QE delivery across multiple vendor or supplier teams within a single domain or program. Proven ability to mentor and develop QA engineers and build a culture of quality ownership. Familiarity with test case management and quality reporting platforms such as TestRail, LambdaTest, or equivalent. Familiarity with large enterprise systems such as ERP, e commerce, and cloud platforms. Experience with AI assisted testing tools in a QE context.