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Open nowPosted 6 days ago

Engineering Manager, QA

Emergent Labs49 open roles

Where
Bangalore
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Your applicationOpen nowEngineering Manager, QAEmergent Labs · Bangalore

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market. Emergent Labs postings stay open a median of 20 days.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 57.8%60 days
This job: posted 6 days ago

Emergent Labs median: 20 days open

The posting

About Emergent

Emergent is building an AI-native platform that enables users to build software using AI. We operate in a fast-paced environment where product quality, customer experience, and release speed are critical.

We are looking for an Engineering Manager, QA, to lead our Quality Assurance function, strengthen testing practices, and ensure consistent product quality across teams. This role requires strong QA fundamentals, people leadership, excellent execution, and the ability to collaborate closely with Engineering and Product teams.

The ideal candidate can build a high-performing QA team, establish effective testing processes, identify risks early, and ensure quality remains a shared responsibility across the organisation.

Responsibilities

Quality strategy and test planning

  • Own the QA strategy and testing approach across product features and releases.
  • Define test plans, test scenarios, coverage expectations, and release-readiness criteria based on product risks.
  • Ensure functional, regression, integration, exploratory, and end-to-end testing are performed effectively.
  • Identify quality risks early during requirement discussions and ensure appropriate test coverage before development is completed.
  • Establish consistent QA processes and standards across product teams.
  • Ensure testing focuses on customer experience, business-critical workflows, and potential production risks.

Release quality and defect management

  • Own QA sign-off and communicate release risks clearly to stakeholders.
  • Drive defect triage, prioritisation, root cause discussions, and follow-up on critical issues.
  • Ensure production defects are analysed and preventive actions are implemented.
  • Monitor defect leakage, regression failures, escaped bugs, and recurring quality issues.
  • Partner with Engineering and Product leaders to make informed release decisions.
  • Balance release timelines with product quality and customer impact.

People management and team development

  • Lead, mentor, and develop QA engineers, helping them improve testing skills, product understanding, and ownership.
  • Set clear expectations, goals, and performance standards for the team.
  • Conduct regular feedback and career development discussions.
  • Hire and onboard QA talent as the organisation grows.
  • Allocate team resources based on product priorities and release commitments.
  • Build a culture of accountability, collaboration, proactive communication, and continuous improvement.
  • Encourage team members to take ownership of quality rather than limiting their responsibilities to executing test cases.

Cross-functional collaboration

  • Work closely with Engineering, Product, and Design teams to ensure requirements are testable and quality risks are identified early.
  • Participate in feature planning, requirement reviews, and release discussions.
  • Ensure QA is involved throughout the development lifecycle rather than only during final validation.
  • Communicate testing progress, blockers, release risks, and quality status to stakeholders.
  • Drive alignment across teams on defect severity, release readiness, and quality expectations.
  • Improve team execution by identifying process bottlenecks and removing unnecessary testing delays.

Continuous improvement

  • Improve test planning, test case quality, regression coverage, and testing efficiency.
  • Identify opportunities to reduce repetitive manual effort and improve QA productivity.
  • Encourage the team to use AI tools where appropriate to support test scenario creation, test documentation, and test analysis.
  • Maintain a basic understanding of automation capabilities and collaborate with SDETs when automation can improve coverage or efficiency.
  • Use quality metrics and production feedback to identify improvement areas and track progress.

Required skills and experience

  • 8–12 years of experience in software QA and testing, with meaningful experience leading or managing QA teams.
  • Strong understanding of software testing methodologies, functional testing, regression testing, exploratory testing, and defect management.
  • Experience managing release quality and making risk-based testing and release-readiness decisions.
  • Proven ability to lead, mentor, and develop QA engineers.
  • Experience working closely with Engineering and Product teams in a fast-paced product environment.
  • Strong understanding of the software development lifecycle, agile delivery, and release processes.
  • Ability to analyse requirements, identify edge cases, and ensure adequate test coverage.
  • Experience tracking quality metrics, analysing defect trends, and driving process improvements.
  • Excellent communication, stakeholder management, prioritisation, and problem-solving skills.
  • Strong ownership and the ability to manage multiple priorities without compromising critical quality standards.

Good to have

  • Basic understanding of test automation concepts and their role in improving testing efficiency.
  • Experience collaborating with SDETs or automation engineers.
  • Familiarity with AI-assisted testing and AI productivity tools.
  • Experience testing SaaS products, AI-powered applications, or complex user workflows.
  • Experience establishing QA processes in a rapidly growing organisation.

Success metrics

  • Reduced production defect leakage and recurring quality issues.
  • Consistent test coverage for critical user journeys and business workflows.
  • Predictable release readiness and timely communication of quality risks.
  • Improved defect detection and resolution before production
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