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Talent Acquisition Lead- Insights & Data Analytics | Asia Pacific + MiddleEast| Diversity and Inclusion | Employer Branding| Banking & Financial…
Who are we? Capgemini Global Insights & Data business line is a market leader in data, platform, and analytics across all regions and many sectors (including financial services, consumer products, manufacturing, and life sciences). Our offerings include end-to-end data integration to a cloud platform, a complete suite of AI engineering capabilities, and a category of sector-based advanced analytics / AI solutions. The Opportunity The Data Quality Assurance Lead will define, plan, and implement testing strategies for GenAI-based products. This role involves planning, overseeing test activities, and ensuring data integrity across system components. The Data Quality Assurance Lead will drive performance, integration, and end-to-end (E2E) testing and support user acceptance testing while collaborating with cross-functional teams to maintain high standards of data accuracy, consistency, and reliability. Our Ideal Candidate Let’s talk about the roles and responsibilities :- Develop and maintain a comprehensive QA strategy, frameworks, and best practices for Generative AI products.
- Define and oversee functional (e.g., UI, system integration, end-to-end, and AI validation) and non-functional (e.g., performance, security, and scalability) testing strategies.
- Work closely with solution architects, developers, and AI specialists to align testing requirements.
- Establish risk assessment processes, ensuring data integrity, AI model performance, and security compliance.
- Ensure successful user acceptance testing activities.
- Lead the implementation of test automation strategies to support continuous testing in CI/CD pipelines.
- Oversee automation frameworks (e.g., Robot Framework, Selenium, Postman) for API and functional testing.
- Robotize processes and best practices for non-functional testing, including performance (e.g., JMeter, LoadRunner) and security validation.
- Led and mentored a team of testers to execute structured test plans and automation frameworks.
- Validate synthetic data generation to align with real-world scenarios for accurate AI testing.
- Ensure acceptance criteria for AI outputs to assess model reliability, fairness, and ethical compliance.
- Monitor test execution, analyse results, and provide insights for AI model improvements.
- Ensure compliance with industry regulations and maintain data security best practices.
- Collect user feedback and recommend enhancements for Generative AI performance and usability.
- A minimum of 8+ years of experience in software quality assurance, with expertise in automation testing and AI-driven systems.
- Good experience in functional and non-functional testing, including automation frameworks (Robot Framework, Selenium, Postman) and performance/security testing tools (Jmeter, LoadRunner).
- Expertise in testing on-premises and cloud environments with AI/ML model validation methodologies.
- Proven leadership and strategic planning skills with experience managing testing teams.
- Familiarity with regulatory compliance standards such as NDMO, PDPL.
- Experience with data validation, synthetic data generation, and AI bias testing.
- Ability to analyze real-world user feedback and recommend model retraining or product improvements.
- Good analytical, problem-solving, and stakeholder management skills.
Seniority level
- Mid-Senior level
Employment type
- Full-time
Job function
- Information Technology
- Industries
- IT Services and IT Consulting and Business Consulting and Services
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