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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.
Job Responsibility:
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-assisted automation, BDD, and API testing, adapting them to the current environment
Acts as an advisor and mentor for junior members of the team, fostering a culture of technical excellence, continuous improvement, and the adoption of AI in quality engineering
Appropriately assesses risk when business decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding Citigroup, its clients, and assets, by driving compliance with applicable laws, rules, and regulations
adhering to Policy
applying sound ethical judgment regarding personal behavior, conduct, and business practices
and escalating, managing, and reporting control issues with transparency
Performs other duties and functions as assigned
Requirements:
6+ years of IT Quality Assurance and Automation Engineering experience required
Strong knowledge and hands-on experience in Java and Spring Boot are mandatory, specifically for developing, debugging, and optimizing robust automation frameworks and testing utilities
Mandatory expertise in API automation using Rest Assured for testing RESTful services, including intricate scenarios involving authentication, data manipulation, and response validation, with an understanding of how AI tools can augment these efforts
Solid understanding and practical application of Behavior-Driven Development (BDD) principles and frameworks (e.g., Cucumber, Gherkin) for creating clear, collaborative, and executable specifications, integrating with AI for enhanced test generation and analysis
Comprehensive grasp of Testing Fundamentals, including various testing types (unit, integration, system, performance, security), AI-assisted test design techniques, the defect lifecycle, and the Systems Development Lifecycle (SDLC)
Proficiency in working with data interchange formats such as JSON and XML, including parsing, generating, and validating these formats within automation scripts, and leveraging AI for schema validation and data integrity checks
Strong experience and knowledge of database technologies, specifically Oracle DB and MongoDB, including advanced SQL querying and NoSQL operations for data validation within automation, potentially guided by AI for complex query optimization
Strong knowledge of branching strategies, DevOps practices, and CI/CD pipelines (e.g., Jenkins, GitLab CI) is mandatory, with extensive experience integrating and optimizing AI-enhanced automation tests into these pipelines
In-depth knowledge, understanding, and analytical thought in complex system architectures and business processes, with an ability to apply AI for system intelligence and predictive quality
Experience and knowledge of Selenium automation is preferred for UI test automation, complementing AI-driven visual testing and UI anomaly detection
Demonstrated ability to assess risk proactively and drive quality with confidence, championing the adoption of new technologies, including AI, in quality engineering
Bachelor’s/University degree or equivalent experience
Master’s degree preferred
Nice to have:
Experience and knowledge of Selenium automation is preferred for UI test automation, complementing AI-driven visual testing and UI anomaly detection
Master’s degree preferred
What we offer:
medical, dental & vision coverage
401(k)
life, accident, and disability insurance
wellness programs
paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays