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Quality Assurance Engineer

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Job Title: Staff Quality Assurance Engineer – LAD

Location: Haifa, Israel Preferred (Onsite)

Full-Time | Pearson Education

About Pearson

Pearson is the world’s leading provider of learning services and materials for higher education institutions and faculties around the globe, operating in over 70 countries.

With a mission to revolutionize the future of learning and courseware , Pearson’s Higher Education team is focused on transforming how students engage with content— developing innovative, consumer-grade digital products that are intuitive, effective, and accessible. We move fast: designing, building, testing, and iterating with agility and purpose.

By putting students at the center of everything we do, we’re creating cross-platform, mobile-first experiences and high-scale web services that are shaping the future of global education.

About the Role:

Pearson is seeking a Staff Quality Assurance Engineer to join our growing, dynamic team. You will help design and develop world-class web applications that are used by millions of learners worldwide.

As a senior team member, you’ll work in a fast-paced, agile environment and take a leading role in quality engineering with strong AI/ML testing experience who can define how Pearson validates intelligent learning systems. The person will own quality strategy for data mapping, APIs, observability, evaluation workflows, and integrations validation.

Key Responsibilities:

  • Define and drive AI Test Strategy: Create comprehensive test strategies specifically for GenAI products and LLM-based workflows, including model accuracy, bias, safety, and reliability validation.

  • Develop and maintain AI testing frameworks, including prompt testing and evaluation of model outputs

  • Build and evolve test automation frameworks, pipelines, and evaluation harnesses for AI/ML models, APIs, and integrated systems.

  • AI-Specific Quality Validation: Design tests around prompt engineering, hallucination detection, model evaluation metrics, and edge-case scenarios.

  • System & Integration Testing: Validate end-to-end workflows, including multi-agent orchestration, MCP models, APIs, and UI interactions.

  • Cross-Functional Collaboration: Partner with Dev, Product, and Data Science to align quality standards with evolving GenAI architectures.

  • Drive defect analysis, implement lessons learned, and adopt emerging tools and methods for testing AI.

Qualifications:

  • 6+ years of experience in Quality Engineering, with at least 3 years in a technical leadership or managerial role.

  • Strong technical expertise in AI/ML product testing, including GenAI workflows, model evaluation, and/or LLM-based solutions.

  • Hands-on experience with test automation frameworks, API/UI testing, and CI/CD pipelines.

  • Familiarity with LLM testing challenges (e.g., prompt variation, non-deterministic outputs, evaluation metrics, model drift).

  • Knowledge of Python or similar languages for building test tools or harnesses.

  • Exposure to prompt engineering, bias testing, or AI ethics frameworks is a plus.

  • Bachelor’s degree in Computer Science, Engineering, or related field (advanced degree preferred).

  • Proven ability to work in cross-functional, Agile/Scrum environments

  • Excellent communication and leadership skills

  • Bachelor's degree in Computer Science, Engineering, or related field; advanced degree is a plus

Why Join Us?

This is an opportunity to shape the future of AI-driven education. You will be at the forefront of defining how AI systems are tested, validated, and trusted in a learning environment that impacts millions of students and instruct

  • Work on products with real impact —millions of users globally

  • Join a startup-like culture within a global leader

  • Collaborate with a tight-knit, talented team

  • Shape the future of digital education ors worldwide.

If you’re passionate about pioneering new approaches to AI testing and want to combine technical leadership with hands-on Quality engineering, this role offers the chance to make a lasting impact.

#LI-MG1

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