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Opening For Automation Testing(Playwright and Typescript must have)

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Opening For Automation Testing(Playwright and Typescript must have)

Acentra Health

Opening For Automation Testing(Playwright and Typescript must have)

Skills

TypescriptPlaywrightMachine LearningAICompliance

2 months ago

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Important information


Contract type:

Permanent

Salary:

₹1,200,000 – ₹2,000,000 / year

Location:

Chennai, Tamil Nadu, India

Work mode:

Hybrid

Published on:

2 September 2026

What they need


Acentra Health is seeking a Staff Quality Engineer to define and drive quality engineering strategy for a product domain, platform, or major healthcare solution area. This role blends deep technical expertise, domain leadership, innovation, architecture influence, and advanced AI-enabled quality engineering practices.

Job Summary and Responsibilities

Define quality engineering strategy, standards, architecture patterns, and measurable quality objectives for a product, platform, or domain.

  • Lead complex testing initiatives such as platform modernization, migration, interoperability, data transformation, large releases, or new product launches.
  • Architect automation ecosystems across UI, API, data, integration, service, performance, security, accessibility, and compliance dimensions.
  • Evaluate, select, and integrate quality tools, autonomous testing capabilities, self-healing automation, and AI-enabled productivity accelerators.
  • Provide technical leadership during architecture reviews, design reviews, testability assessments, operational readiness, and release governance.
  • Influence cross-team quality standards, documentation, reusable frameworks, shared services, and engineering best practices.
  • Mentor Senior Quality Engineers and contribute to communities of practice, technical guilds, publications, demos, and knowledge assets.
  • Partner with security, compliance, product, engineering, operations, and client-facing teams to ensure healthcare quality requirements are addressed early.
  • Use data and metrics to identify systemic quality trends, investment priorities, ROI opportunities, and quality transformation outcomes.

Job Requirements and Qualifications

Required Qualifications

  • 10-12 years of experience in quality engineering, software engineering in test, automation architecture, or related technical leadership roles.
  • Expert-level automation framework design and hands-on engineering experience across multiple application and service layers.
  • Advanced understanding of AI/ML testing practices, autonomous testing concepts, self-healing automation, and responsible AI governance.
  • Experience leading quality strategy for complex, regulated, mission-critical, or highly integrated systems.
  • Strong knowledge of performance engineering, security testing, compliance-aware testing, and production quality signals.
  • Proven ability to influence architecture, standards, technical direction, and cross-functional execution without direct authority.
  • Strong business acumen, communication, technical writing, and stakeholder influence skills.

Preferred Qualifications

  • Healthcare technology experience across payer, provider, clinical, case management, claims, eligibility, interoperability, or government health systems.
  • Experience contributing to shared quality platforms, engineering enablement, innovation labs, patents, publications, or conference presentations.
  • Advanced certification in AI-QE, cloud, security, performance engineering, or test architecture.

AI and Automation Expectations

  • Design autonomous testing ecosystems; apply agentic AI workflows and multi-LLM orchestration where approved; establish responsible AI testing patterns and governance guardrails.

Success Measures

  • Quality strategy adopted across product/domain teams with measurable improvements.
  • Reusable automation, platforms, or tools that improve speed, coverage, reliability, and compliance confidence.
  • Successful delivery of complex healthcare initiatives with clear risk visibility and reduced production issues.
  • Visible technical leadership through standards, mentoring, thought leadership, and cross-team influence.
  • Responsible AI-QE adoption with governance, traceability, and value measurement.

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