Job Description
Posted Date 5/08/2026 Description The Java Automation Senior Manager (IT Quality Senior Manager - C13) is responsible for delivering exceptional quality outcomes through hands-on automation engineering, comprehensive testing strategies, and robust technical assurance. This role requires deep subject-matter and industry expertise within a defined technology domain, contributing to establishing and championing AI-assisted quality engineering practices and delivery standards across broader teams. The position demands an in-depth understanding of how various technology and quality processes integrate to support overall functional and organizational objectives, with a keen eye on optimizing these processes through intelligent automation. Basic commercial awareness is needed to understand the broader impact of technical decisions. Strong communication, collaboration, and diplomacy skills are essential. The individual will work closely with cross-functional partners—often influencing and guiding colleagues in other areas and occasionally external stakeholders—to ensure alignment on AI-driven quality standards and delivery expectations. This role is accountable for the quality, accuracy, timeliness, and completeness of assigned deliverables, specifically focusing on automated validation and AI-enhanced insights. The individual may also contribute to planning activities, process improvements leveraging AI, and policy or standards development within their area of expertise. Responsibilities: Designs, develops, and enhances robust and scalable automation testing frameworks in Java and Spring Boot environments, analyzing both functional and non-functional requirements to ensure comprehensive coverage. This is a highly hands-on automation engineering role. Implements and maintains advanced API automation suites using Rest Assured for thorough testing of RESTful and other web services, integrating AI-assisted anomaly detection and validation techniques. Applies Behavior-Driven Development (BDD) principles to craft clear, executable specifications (e.g., Gherkin), collaborating closely with product owners and developers to ensure shared understanding and AI-enhanced test case generation. Develops and executes advanced SQL queries for Oracle DB and interacts with MongoDB for efficient data setup, validation, and verification within automation scripts, potentially leveraging AI for complex data pattern identification. Leads initiatives related to the User Acceptance Testing (UAT) process and product rollout into production, including the design and implementation of appropriate automation scripts and AI-driven insights for an application testing strategy. Conducts a broad range of complex process monitoring, product evaluation, and audit assignments , focusing on areas requiring deep technical insight and utilizing AI-powered analytics to identify potential risks and areas for improvement. Collaborates seamlessly with local and global stakeholders , such as the QA team, production support team, environment management team, and DBA team, to ensure project stability and productivity through effective automation and AI-driven predictive quality. Ensures project standards and procedures are fully and clearly documented and followed throughout the software development life cycle, emphasizing AI-driven quality gates for automation and continuous feedback loops. Monitors products for conformance to standards and processes for conformance to procedures; identifies risks and ensures annual organizational reviews of standards and procedures are conducted, using AI to flag deviations and suggest corrective actions. Documents findings and performs root cause analyses , leveraging AI-assisted tools for faster identification of underlying issues, recommending solutions and improvements to existing standards and procedures; collaborates with other technology areas to develop new, AI-informed standards and procedures. Ensures all corrective actions are assigned, documented, and completed in a timely manner, with AI potentially tracking resolution progress. Verifies traceability in project work products , linking requirements to test cases and defects, potentially using AI to ensure comprehensive coverage and identify gaps. Gathers, maintains, and reports on quality metrics , including automation coverage, defect trends, and overall application health, utilizing AI for advanced analytics and predictive insights into quality. Continuously researches and applies industry quality trends and best practices in AI-a