Delivery Quality Lead - GenAIAbout the role The Delivery Quality & Engineering (DQ&E) team is responsible for overall Delivery Quality and successful implementation of AIG's product and features to our customers. The organization while delivering quality assurance services should ensure collaboration, planning, engagement and execution working closely with diverse teams including Application Delivery, Business Operations, Technology Support and Product Management. The Delivery Quality & Engineering teams will need Subject Matter Expertise that focuses on quality requirements, technical engineers focusing on solutions that accelerate the testing lifecycle and strong management skills to coordinate and deliver programs working with multi-disciplinary teams and global execution model.
Primary focus areas for Delivery Quality & Engineering include Lifecycle Automation, Business Centric Testing & Engineering driven assurance, End-User Experience long with Digital Assurance.
The Delivery Quality Lead role is critical to the success of the Delivery Quality & Engineering organization. The individual is required to have a deep understanding of Quality Assurance and Engineering (QA&E) practices and principles, solutions, frameworks and continuous testing capabilities to lead the specific capabilities of the DQ&E Organization.
How you will create an impactThe Delivery Quality Lead plays a pivotal role in ensuring the delivery of high-quality software products and services. They are also responsible for accuracy and reliability of the organization's data assets. By leading a team of skilled testers and executing a robust testing plan,, this role contributes to maintaining the highest standards of application quality across various business processes in addition to ensuring compliance with regulatory requirements and best practices
- Develop and implement testing strategies, methodologies and best practices catered towards GEN AI and traditional AI technologies.
- Implementation of GenAI solution to improve testing strategies and plan.
- Create detailed test plans, including test scope, objective, resource planning and schedules.
- Review designing test cases, scenarios and automation scripts to validate data accuracy and integrity. Identify and prioritize critical data elements for testing.
- Lead the testing team in executing data quality tests according to defined plans.
- Report any deviations / risks to the leadership with right details.
- Ensuring that the team performs high quality data validation, reconciliation, and data transformation testing.
- Work with the teams to document defects, inconsistencies, and anomalies in data sets.
- Evaluate opportunities for test automation to enhance testing efficiency.
- Implement and maintain automated testing scripts and frameworks.
- Monitor automated test execution and analyze results for accuracy.
- Work closely with data engineers, data analysts, and data stewards to understand data structures and relationships.
- Develop and manage test artifacts, metrics and reports for QA activity to align to executive communication needs.
- Identify and document key risk items related to quality and present to program
- Collaborate with business analysts to understand data requirements and use cases.
- Coordinate testing efforts across cross-functional teams to ensure comprehensive coverage.
- Generate test summary, execution reports and metrics to communicate testing results.
- Provide actionable insights to stakeholders based on test findings.
- Contribute to continuous improvement efforts that will enhance data quality processes.
- Identify areas for process improvement in data quality testing.
- Implement measures to prevent data quality issues and ensure proactive detection.
- Enhance testing methodologies based on lessons learned and industry standards.
- Manage and mentor a team of data quality testers and analysts.
- Provide guidance, training, and performance evaluations for team members.
- Foster a collaborative and innovative work environment.
- Work closely with the DevOps, compliance, audit and engineering teams to adhere to the established process and standards.
What you'll need to succeed- Bachelor's / Master's degree in Computer Science, Information Technology, or related field (Master's preferred).
- 8+ years experience in data quality testing and quality assurance roles.
- Strong automation experience using automation frameworks and hands on experience with Selenium, Cucumber.
- Working experience on building technology solutions leveraging GenAI
- Strong understanding of data quality frameworks and best practices.
- Familiarity with data profiling, data cleansing, and data enrichment techniques.
- Excellent analytical and problem-solving abilities.
- Effective communication and interpersonal skills.
- Leadership experience and the ability to lead and motivate a team.
- Knowledge in Snowflake, ETL tools, Python, AWS preferred.
- DevOps Tools and process knowledge.
- Any experience in testing GenAI.
- Knowledge on prompt engineering
- Strong understanding of SAFe Agile and QA methodologies.
- Excellent communication and leadership skills.
Veterans are encouraged to apply.
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At AIG, we value in-person collaboration as a vital part of our culture, which is why we ask our team members to be primarily in the office. This approach helps us work together effectively and create a supportive, connected environment for our team and clients alike.
Enjoy benefits that take care of what mattersAt AIG, our people are our greatest asset. We know how important it is to protect and invest in what's most important to you. That is why we created our Total Rewards Program, a comprehensive benefits package that extends beyond time spent at work to offer benefits focused on your health, wellbeing and financial security-as well as your professional development-to bring peace of mind to you and your family.
Functional Area:
IT - Information Technology
AIG PC Global Services, Inc.
