[Hiring] Quality Engineer @Zensar

Role Description

As Quality Engineering Lead, you’ll drive uncompromising reliability and intelligent automation, using AI-powered insights and automation-first engineering to ensure our platform’s excellence and robust validation at every layer.

• Design, build, and maintain automation frameworks for UI, API, data, and microservices testing.
• Leverage AI-driven techniques for test generation, defect detection, and regression selection.
• Develop and track observability-based quality metrics and CI/CD quality gates.
• Validate AI/ML-powered features and collaborate to ensure safe and correct model behavior.
• Define and implement end-to-end quality strategies across key platform components.
• Partner with engineering, product, and SRE teams to ensure strong SDLC testability and guardrails.
• Lead and mentor a quality engineering team, fostering AI-assisted engineering practices.
• Drive technical excellence through standards, code reviews, and continuous skill development.

Qualifications

• Bachelor's degree in Computer Science or equivalent experience.
• 7+ years of direct experience in software quality engineering, including automation architecture and framework development.
• Strong hands-on expertise with modern automation tools (Playwright, Selenium, JUnit/TestNG, Postman et al).
• Proven experience validating AI-enabled features — LLMs, anomaly detection, model-driven logic, or generative workflows.
• Deep knowledge of testing for distributed systems, microservices, data pipelines, and cloud environments (AWS preferred).
• Solid experience integrating automation into CI/CD pipelines.
• Strong debugging, problem-solving, and analytical skills across frontend, backend, and data layers.
• Excellent communication, collaboration, and cross-team influence skills in a fast-paced engineering organization.

Requirements

• Experience with RAG pipelines, vector stores, guardrail frameworks, model evaluation, or safe AI patterns.
• Experience testing financial systems, billing engines, or analytics-heavy platforms.
• Familiarity with synthetic data generation or statistical validation for AI and data-driven testing.

Benefits

• Flexible and creative work environment.
• Diverse and collaborative atmosphere.
• Professional and personal development resources.
• Opportunities to volunteer and support charities.
• Competitive salary and benefits.