Senior Software Quality Engineer - AI Assurance

Hot Duties:

Build and scale next-generation products through AI-powered testing, intelligent automation, and continuous AI assurance. Demonstrate good proficiency in Automation-First and Specs-Driven Testing (SDT), transforming requirements into verifiable specifications, automated tests, and measurable quality outcomes. Apply AI agents, LLMs, MCP, autonomous test generation, and self-healing automation to accelerate engineering velocity, expand coverage, and improve release confidence across Web, Mobile, APIs, and AI-powered applications. Drive continuous evaluation, red teaming, risk-based validation, and AI governance to ensure intelligent products and autonomous workflows remain reliable, secure, resilient, and aligned with business intent.

Duties:

• Design, develop, and evolve scalable automation frameworks for Web, Mobile, APIs, and AI-powered applications
• Drive AI-Powered Testing, Specs-Driven Testing (SDT), Automation-First, and Shift-Left practices to accelerate delivery and improve quality
• Use AI coding assistants, LLMs, and AI agents for test generation, test data creation, optimization, defect analysis, and self-healing automation
• Translate business requirements and specifications into executable tests, integrating automated quality gates into CI/CD pipelines
• Execute API, performance, accessibility, security, regression, and end-to-end testing based on business and technical risks
• Drive AI Assurance through continuous evaluation, red teaming, and validation of LLMs, RAG systems, multimodal applications, and autonomous agents
• Assess AI systems for accuracy, hallucinations, bias, security, reliability, resilience, and responsible behavior
• Define quality metrics, AI trust indicators, governance controls, and release-readiness practices to enable safe and reliable AI adoption
• Collaborate with engineering, product, and client teams to manage risks, communicate outcomes, and continuously improve quality
• Mentor engineers in modern quality engineering, AI-assisted testing, and emerging AI Assurance practices

Requirements:

• Proficiency in Java, Python, or JavaScript/TypeScript, with hands-on experience in Selenium, Playwright, or equivalent automation frameworks
• Experience with JUnit, TestNG, or equivalent testing frameworks and CI/CD platforms such as Jenkins or GitLab CI/CD
• Using AI coding assistants such as Claude, Cursor, GitHub Copilot, Gemini Code Assist, or equivalent tools
• Good understanding of AI-Powered Testing, Specs-Driven Testing (SDT), Shift-Left practices, risk-based testing, and test automation strategy
• Ability to translate requirements and business intent into executable specifications, comprehensive test scenarios, and measurable quality outcomes
• Understanding of LLMs, AI agents, RAG, prompt engineering, autonomous workflows, and AI-assisted automation
• Good analytical, problem-solving, communication, and stakeholder-management skills with a focus on quality ownership
• Optional: Familiarity with API testing (Postman/REST Assured), performance testing (JMeter), accessibility testing (axe/WAVE/Lighthouse), or mobile automation
• Optional: Ability to evaluate AI outputs for accuracy, hallucinations, bias, security, reliability, and alignment with expected behavior
• Optional: Exposure to MCP, AI evaluation frameworks, red teaming, AI observability, trust measurement, responsible AI, and security or compliance governance