GenAI Test Architect Job Opportunity

Job Summary:
We're searching for a GenAI Test Architect to lead the design, development, and deployment of a GenAI-based QA automation strategy. This pivotal role will establish an AI-driven automation framework that integrates across our diverse product lines, ensuring superior product quality and optimized development processes. The ideal candidate will have exceptional technical expertise in QA automation and strategic knowledge of General AI applications, revolutionizing our testing efficiency and accuracy.

Key Responsibilities:

• Design and implement a robust, scalable GenAI-based QA automation strategy supporting Windows, iOS, cloud services, and firmware development.
• Collaborate with data scientists, software development teams, and other AI professionals to align the AI-based approach with ecosystem quality.
• Standardize QA processes and tools across all teams by integrating GenAI technologies to automate testing tasks and minimize manual effort.
• Align technical architecture and implementation with existing and future requirements by gathering inputs from product managers, users, data scientists, engineers, and IT operations.
• Play a key role in defining AI architecture and selecting suitable open-source and commercial technologies.
• Evaluate and select third-party GenAI QA automation tools and services to align with our technological environment.
• Create and maintain comprehensive documentation of the QA automation framework, tools, and best practices.
• Educate and mentor team members in GenAI-based testing techniques, tools, and best practices.
• Stay updated on advancements in AI, machine learning, and QA technologies to refine our QA automation strategy.
• Assess and enhance the performance of the QA automation framework to ensure high efficiency and reliability of testing operations.
• Foster collaboration among software development, QA, and IT operations teams to ensure an integrated approach to product quality and release cycles.

Required Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a relevant field with a focus on software quality assurance.
• 5-8 years of experience in QA automation with significant expertise in developing and executing QA automation strategies.
• Proven experience with GenAI technologies in QA automation.
• Proficiency in automation tools and frameworks, understanding testing across Windows, iOS, cloud platforms, and firmware environments.
• Comprehensive knowledge of software development life cycles, Agile methodologies, and DevOps/MLOps practices.
• Strong problem-solving skills and creativity in a dynamic work setting.
• Exceptional communication and leadership skills with the ability to guide cross-functional teams.

Education & Experience Recommended:

• Four-year or Graduate Degree in Computer Science, Information Systems, or a related discipline, or equivalent work experience.
• Typically, 10+ years of work experience in systems engineering, computer programming, or a related field.

Preferred Qualifications:

• Advanced degree in Computer Science or a related field.
• Certifications relevant to QA methodologies, Agile, or project management.
• Experience with machine learning models in testing scenarios.
• In-depth knowledge of QA automation processes and practices.

Knowledge & Skills

• Experience in designing and developing software and cloud systems.
• Expertise in designing and testing highly scalable, reliable systems.
• Experience leading test automation framework design and deployment.
• Thorough knowledge of AI concepts (NLP, deep learning, ML) and related adjacencies.
• Proficiency in AI frameworks like PyTorch and programming languages such as Python, Java, C++.
• Experience with data engineering and distributed computing frameworks.

Cross-Org Skills

• Effective Communication
• Results Orientation
• Learning Agility
• Digital Fluency
• Customer Centricity

Impact & Scope

Impacts large functions and leads large, cross-division functional teams or projects.

Complexity

Provides highly innovative solutions to complex problems