Automation Lead

AI-Driven Quality Engineering Leadership

AI-Focused Quality Engineering Center of Excellence

Coaching & Enablement

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent experience.
• 10+ years of Quality Assurance experience supporting complex applications.
• 7+ years of hands-on test automation experience using tools such as Playwright, Selenium, Cypress, Cucumber, Java, C#, or similar technologies.
• Proven success in evaluating and implementing AI-enabled quality engineering solutions.
• Experience developing and maintaining automation frameworks and testing solutions.
• Experience leading automation initiatives or mentoring Quality Engineering teams.
• Experience with cloud-based platforms and modern DevOps practices.
• Experience with UI, API, integration, and headless test automation.
• Experience working in Agile environments with CI/CD practices.
• Strong communication, problem-solving, and collaboration skills.
• Business Unit:
• Property & Casualty IT Services

Benefits:

• We offer competitive benefits packages for full-time and part-time employees. Full-time employees have access to medical, dental, and vision coverage, wellness plans, parental leave, adoption assistance, and tuition reimbursement. Full-time and eligible part-time employees also enjoy Paid Time Off and paid holidays, a 401(k) plan with company match, an employee stock purchase plan, and commuter benefits.
• Compensation varies by role, level, and location and is influenced by skills, experience, and business needs. Your recruiter will provide details about benefits and specific compensation ranges during the hiring process. Learn more at http://www.gaig.com/careers.
• Excludes seasonal employees and interns.

Responsibilities

• Serve as a subject matter expert for AI-enabled Quality Engineering, intelligent automation, and modern testing practices.
• Lead the evaluation, adoption and scaling of AI-assisted Quality Engineering transformation through continuous testing, automation modernization and AI-enabled testing capabilities across the SDLC.
• Identify opportunities to leverage AI to accelerate test design, automation development, defect analysis, and quality insights to improve testing efficiency and productivity.
• Define and promote AI-enabled automation standards, frameworks, best practices, and governance focusing on emerging technologies and industry trends.
• Evaluate and implement AI-assisted testing capabilities, such as: automated test generation, self healing automation, risk based testing, defect prediction and analysis.
• Partner with Quality Engineering leadership to mature enterprise CoE capabilities.
• Create reusable assets, playbooks, standards, templates, and implementation guides.
• Develop adoption strategies for AI and automation across multiple technology organizations.
• Measure effectiveness and value realization of enterprise quality initiatives.
• Establish and monitor KPIs related to automation adoption, AI utilization, engineering productivity, and quality outcomes.
• Mentor Quality Engineers on emerging technologies and modern testing practices.
• Develop training programs, workshops, technical guidance, and educational materials.
• Build organizational awareness and understanding of AI-enabled Quality Engineering capabilities.
• Foster a culture of innovation, experimentation, technical excellence, and continuous learning.
• Act as a trusted advisor to engineering teams implementing AI and automation solutions.