Quality Engineering Leadership

Role Overview

Provide enterprise-wide leadership, vision, and strategic direction for Quality Engineering (QE), establishing an automation-first quality strategy that improves test coverage, release confidence, engineering productivity, cost effectiveness, and speed to market across a complex technology portfolio.

The role will define and execute a multi-year Quality Engineering strategy aligned with business objectives, Core Technology priorities, modernization initiatives, regulatory requirements, and enterprise risk expectations. This position will lead the modernization of the QE ecosystem, drive continuous quality across Agile and DevOps delivery, and establish scalable, measurable, and AI-enabled quality practices across the organization.

Key Responsibilities

- Provide leadership, vision, and strategic direction for Quality Engineering, establishing an enterprise-wide automation strategy that improves test coverage, release confidence, engineering productivity, and speed to market.
- Define and execute a multi-year Quality Engineering strategy and roadmap aligned with business outcomes, Core Technology priorities, modernization objectives, and enterprise risk expectations.
- Establish and govern enterprise testing standards, operating procedures, quality gates, metrics, and KPI frameworks across multiple products and technology platforms.
- Use portfolio-level quality insights and metrics to identify risks, drive corrective actions, improve release readiness, and communicate quality performance to senior leadership.
- Provide horizontal Quality Engineering leadership across multiple programs, partnering with product, engineering, architecture, operations, business, and strategic vendor stakeholders to align priorities, manage dependencies, standardize delivery practices, and achieve consistent quality outcomes.
- Build trusted partnerships with senior product, engineering, architecture, DevOps, Site Reliability Engineering (SRE), security, operations, and business leaders to translate portfolio priorities, application risks, and regulatory requirements into fit-for-purpose quality strategies and investment decisions.
- Lead the modernization of the Quality Engineering ecosystem through scalable automation frameworks, API and service-level testing, cloud-enabled test environments, service virtualization, test data management, and AI-assisted testing capabilities.
- Establish an automation-first engineering culture by promoting reusable frameworks, testability, continuous testing, shift-left and shift-right practices, and measurable quality outcomes.
- Embed continuous quality within Agile and DevOps delivery by integrating automated functional and non-functional testing into CI/CD pipelines, establishing risk-based quality gates, and accelerating feedback throughout the software delivery lifecycle.
- Drive large-scale UI, API, backend, integration, performance, resilience, security,



and non-functional testing strategies across enterprise applications and distributed systems.
- Partner with Engineering, DevOps, SRE, Security, and Operations teams to define and validate performance, availability, resilience, security, observability, and capacity requirements.
- Leverage production insights, operational data, and quality metrics to identify systemic risks and drive preventive quality improvements.
- Establish and govern risk-based testing strategies across multiple products, platforms, and enterprise portfolios, ensuring appropriate quality coverage based on business and technology risk.
- Drive measurable improvements in testing productivity, cost effectiveness, release confidence, and speed to market by expanding risk-based automation, reducing manual regression effort, optimizing tools and vendors, and tracking portfolio-level value realization.
- Evaluate, govern, and scale AI-enabled Quality Engineering use cases, ensuring appropriate controls for security, privacy, human oversight, adoption, productivity improvement, and measurable business value.
- Lead and develop cross-functional Quality Engineering teams in a global, matrixed environment, building technical capabilities and coaching leaders and teams on modern QE practices.
- Manage strategic technology and testing vendors within an onshore/offshore delivery model, ensuring delivery quality, operational effectiveness, commercial value, and alignment with enterprise QE objectives.

Required Qualifications
- Solid leadership, communication, collaboration, negotiation, and stakeholder management skills, with the ability to influence stakeholders at all levels of the organization.
- Proven experience managing and developing cross-functional Quality Engineering / QA teams within Agile and DevOps environments.
- Expertise in Quality Engineering strategy, enterprise automation strategy, continuous testing, and AI-assisted testing methodologies.
- Proven ability to define and implement large-scale QA and testing strategies across UI, API, backend, integration, and distributed enterprise systems.
- Strong experience building automation-first engineering cultures and establishing reusable testing frameworks, testability practices, continuous testing, and measurable quality outcomes.
- Experience evaluating, governing, and scaling AI-enabled Quality Engineering use cases, with demonstrated accountability for security, privacy, human oversight, adoption, productivity gains, and value realization.
- Strong experience influencing senior Product, Engineering, Architecture, DevOps, SRE, Security, Operations, Business,



and Vendor stakeholders within a global, matrixed organization.
- Experience managing strategic testing and technology vendors in an onshore/offshore delivery model.
- Experience designing and implementing enterprise-scale testing architectures, frameworks, and solutions.
- Experience building an automation strategy and Quality Engineering operating model from the ground up.

Healthcare IT Experience
- Significant experience in Healthcare IT, with a strong understanding of healthcare industry terminology, business processes, regulatory requirements, data privacy, security, and compliance.
- Experience with healthcare claims adjudication and end-to-end claims lifecycle processes, including quality risks associated with high-volume and highly regulated transaction systems.
- Understanding of healthcare data privacy, security controls, audit requirements, and regulatory considerations relevant to enterprise application quality.

Required Experience & Education
- 18+ years of experience across Software Development Life Cycle (SDLC), Quality Engineering, QA, or related technology disciplines.
- 10+ years of experience in people management, technical leadership, and developing high-performing engineering teams.
- Proven experience leading enterprise-wide Quality Engineering transformation and large-scale testing initiatives.
- Experience with vendor management and distributed/onshore-offshore delivery models.
- Expertise in architecture, design, and development of large-scale enterprise testing solutions.
- Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field, or equivalent professional experience.

Desired Experience
- Experience defining and governing end-to-end testing lifecycles, Quality Engineering operating models, quality standards, and risk-based testing strategies across multiple products, platforms, or enterprise portfolios.
- Experience establishing Quality Engineering strategies for cloud-native and distributed systems, preferably within AWS environments.
- Experience validating cloud-native applications across resilience, scalability, security, performance, observability, availability, and failure-recovery scenarios.
- Experience with service virtualization, test data management, API/service-level testing, performance engineering, and automated non-functional testing.
- Experience integrating automated quality practices into CI/CD pipelines and implementing shift-left and shift-right testing strategies.
- Experience applying AI-assisted testing and generative AI capabilities to improve test design, automation, defect detection, regression coverage, and engineering productivity.
- Experience establishing enterprise QE metrics, quality KPIs, governance frameworks, and value-realization models.
- Experience working within highly regulated environments where data privacy, security, auditability, and compliance are critical.

📌 Associate Director - Quality Engineering (Hyderabad)
🏢 Careernet
📍 Hyderabad