AI Test Automation Architect

About Client :

Our client is an 𝐀𝐈-𝐟𝐢𝐫𝐬𝐭, 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦-𝐥𝐞𝐝 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐂𝐨𝐦𝐩𝐚𝐧𝐲 headquartered in Pittsburgh. At the core is our mission to enhance lives by transforming businesses through innovation. We focus on applying next-generation technologies to solve complex challenges and accelerate enterprise transformation. With a global presence across 23 locations and a team of 4,200+ employees, including 1,000+ trained in AI and GenAI, we help organizations modernize through a unique blend of engineering excellence, proprietary IP, and proven execution models. Our delivery methodology is built on a strong operational framework and a mature governance model that fosters true partnership and joint ownership through equal investments.

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Automation AI QA Lead Requirement

Role Overview The Automation QA Lead will spearhead the AI-augmented testing and automation strategy, enabling automation lifecycle phases through AI and GenAI capabilities. This includes requirement analysis, test design, automation scripting, execution, and self-healing — all leveraging AI-based tooling. The role focuses on building a custom AI-driven QA framework, not just adopting existing solutions.

Key Responsibilities

Lead automation architecture and strategy, focusing on AI/GenAI integration in testing workflows. Define and design an intelligent test automation ecosystem that includes: AI-driven requirement analysis and test case generation. AI-assisted test script creation and self-healing automation. Automated execution orchestration and results analysis. Evaluate and integrate various AI frameworks and tools (e.g., Google Vertex AI, Gemini, or other LLMs). Ensure the system remains LLM-agnostic, capable of switching between Gemini, OpenAI, or other models with minimal rework. Work on AI-based problem statement identification and solution design across multiple domains. Collaborate with architects to define scalable, reusable automation frameworks integrated with CI/CD pipelines. Drive performance, quality, and automation efficiency through intelligent test management and data evaluation. Oversee a cross-domain QA team (approx. 5–6 members including architects, testers, and automation engineers).

Must-Have Skills

Strong experience in test automation leadership and architecture. Knowledge of AI/GenAI concepts applied in QA: prompt-based automation, self-healing, intelligent test generation. Hands-on experience with tools like Selenium, Playwright, Cypress, and Python/Java-based automation frameworks. Familiarity with LLM APIs and AI orchestration (Vertex AI, Azure OpenAI, LangChain, etc.). Experience designing frameworks adaptable across multiple domains and tools. Excellent understanding of test data management, execution pipelines, and AI governance in QA. Preferred Qualifications Strong architectural mindset – ability to translate technical problem statements into framework design. Experience with agentic AI-based testing solutions (building autonomous QA agents). Prior exposure to DevOps integration and test intelligence dashboards. Thought leadership on AI-driven testing practices and emerging automation ecosystems.