Hybrid Lead Quality Assurance Engineer

at Pearson VUE

• Job title: Lead Quality Assurance Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Cypress, Java, Jenkins, JMeter, Python, SDLC, Selenium
• Location requirements: Hybrid, India

About the role

• Technical Lead in Quality Assurance leading QA initiatives across software and next-gen AI. Responsible for QA strategy, team mentoring, and process improvement.

Responsibilities

• Define and execute QA strategy across software products including GenAI agents, LLM-based tools, APIs, and web/mobile applications.
• Establish and monitor quality goals, test coverage, release readiness, and risk-based validation plans for AI and traditional systems.
• Drive test architecture and frameworks for both functional and AI-specific evaluations.
• Ensure best practices in STLC, SDLC, Agile methodologies, and CI/CD processes.
• Maintain and report test execution metrics, defect leakage, test effectiveness, and quality KPIs.
• Collaborate with cross-functional stakeholders across engineering, product, and data science teams to align quality goals.
• Manage, mentor, and grow a team of QA engineers, automation experts, and analysts.
• Conduct performance reviews, skill-gap analysis, and career planning for team members.
• Support recruitment, onboarding, and scaling of the QA team.
• Foster a culture of continuous improvement, innovation, accountability, and learning.
• Facilitate effective internal and external communication regarding project updates, risks, and timelines.
• Lead development of test automation strategies using tools such as Selenium, Playwright, Cypress, Robot Framework.
• Integrate automation into CI/CD pipelines using tools like Jenkins, GitHub Actions, etc.
• Design and maintain performance testing frameworks using tools such as JMeter, LoadRunner, and SoapUI.
• Incorporate GenAI-specific test tools like DeepEval, PromptLayer, and LLM observability tools into automation pipelines.
• Apply basic scripting knowledge (Python/Java) for framework customization and tool integration.
• Design robust evaluation frameworks for GenAI/LLM systems including: Output accuracy, hallucination detection, factual consistency.
• Prompt testing, adversarial scenarios, and edge case validation.
• Collaborate with AI/ML teams to define evaluation hooks, model behaviors, benchmarking standards, and observability.
• Use AI to generate and maintain test scenarios for intelligent systems.

Requirements

• Bachelor’s/Master’s degree in Computer Science, Engineering, or related field.
• 10+ years of QA experience with at least 4+ years in a leadership/managerial capacity.
• Proven experience in building and scaling automation frameworks and QA practices.
• Hands-on experience with Generative AI model behaviors (e.g., GPT-4, Claude, RAG pipelines, LLMs).
• Strong understanding of Agile/Scrum methodologies, DevOps pipelines, CI/CD processes.
• Familiarity with test management tools and requirement traceability processes.
• Ability to interpret and assess software requirements, perform impact analysis, and contribute to high-quality test design.
• Deep understanding of quality assurance artifacts including test plans, test cases, test data, and defect life cycle.

Benefits

• This role offers a unique opportunity to be at the forefront of software quality assurance — combining traditional QA excellence with AI-driven innovation. If you're passionate about quality and future-facing technologies, we'd love to hear from you.