Responsibilities- • Design and implement a robust, scalable GenAI-based QA automation strategy that supports Windows, iOS, cloud services, and firmware development, ensuring seamless integration and scalability across these platforms. • Collaborate with data scientists, software development teams and other AI professionals gather insights into their testing needs and challenges, guaranteeing that the AI based approach in driving Ecosystem quality. • Standardize QA processes and tools across all teams, integrating GenAI technologies to automate testing tasks, minimize manual effort, and identify issues earlier in the development lifecycle. • Align technical architecture, design and implementation with existing and future requirements by gathering inputs from multiple stakeholders - product and program management, users, data scientists and engineers and analysts, and those in IT operations - and developing processes and products based on the inputs. • Play a key role in defining the AI architecture and selecting appropriate t echnologies and tools from a pool of open-source and commercial offerings. Select cloud, on-premises or hybrid deployment models, and ensure new tools are well-integrated with existing data management and analytics tools. • Evaluate and select third-party GenAI QA automation tools and services, ensuring they align with our technological environment and testing requirements. • Create and maintain comprehensive documentation of the QA automation framework, tools, and best practices, promoting knowledge sharing and uniform implementation across teams. • Educate and mentor team members in GenAI-based testing techniques, tools, and best practices, elevating the QA capabilities within the organization. • Keep up with advancements in AI, machine learning, and QA technologies to continually refine our QA automation strategy with state-of-the-art tools and methods. • Assess and enhance the performance of the QA automation framework to guarantee high efficiency, effectiveness, and reliability of testing operations. • Promote cooperation among software development, QA, and IT operations teams to ensure an integrated approach to product quality and release cycles. • Designing and testing of highly scalable, reliable systems •Qualifications: • Experience in QA automation, including substantial expertise in formulating and executing QA automation strategies. • Proven track record with GenAI technologies and their application in QA automation. • Proficiency in automation tools and frameworks, with a comprehensive understanding of testing in Windows, iOS, cloud platforms, and firmware environments. • In-depth knowledge of software development life cycles, Agile methodologies, and DevOps/MLOps practices. • Strong problem-solving abilities and creativity in a dynamic work setting. • Exceptional communication and leadership skills, with the capacity to guide cross-functional teams and spearhead initiatives. • Certifications relevant to QA methodologies, Agile, or project management. • Experience with machine learning models and applying them in testing scenarios. • Knowledge of QA automation processes and practices. • Thorough knowledge of AI concepts (NLP, deep learning, ML and related adjacencies) • Data Engineering and distributed computing frameworks • Proficiency in AI frameworks like PyTorch and languages like Python, Java, C++