LPL Financial is looking to enhance its engineering best practices, tools, design patterns, and frameworks by integrating AI-based quality gates and observability into CI/CD pipelines. The goal is to improve product quality and release velocity through advanced testing methodologies and automation.
Requirements
- Advanced concurrent programming skills in Java/Python.
- Experience with AI-assisted development tools.
- Designing and building scalable automation frameworks, with a focus on integrating AI/ML for intelligent test generation and maintenance.
- API testing (SOAP and REST/Microservices), including the use of AI tools for contract validation and anomaly detection.
- Experience with test frameworks such as JUnit, TestNG, and tools for UI/Mobile testing, enhanced by AI-based visual validation and test optimization.
- Proven experience with CI/CD pipelines, including integration of AI for test impact analysis, release risk prediction, and automated quality gates.
- Strong SQL expertise, capable of writing complex queries and leveraging AI for data validation, anomaly detection, and test data generation.
Responsibilities
- Integrate AI-based quality gates and observability into CI/CD pipelines.
- Create and maintain synthetic and production-like data scenarios using AI-powered data generation tools to support comprehensive test coverage.
- Develop and automate test cases, and drive continuous improvement in product quality and release velocity.
- Apply diverse software testing methodologies—including AI-driven test generation and predictive analytics—to ensure robust and scalable software delivery.
- Coordinate and lead end-to-end (E2E) testing efforts across domains, leveraging AI tools for test orchestration, anomaly detection, and intelligent defect triaging.
- Identify manual processes and implement intelligent automation solutions using AI/ML frameworks to optimize testing efficiency and reduce cycle time.
- Analyze test results using AI/ML models to detect patterns, predict defect-prone areas, and proactively improve test strategies.
Other
- Master’s or Bachelor’s Degree in Computer Science or a related field, with a strong foundation in software engineering principles and AI/ML fundamentals.
- Minimum of 10 years of hands-on experience in software development and test automation.
- Minimum of 6 years of leadership experience managing multiple initiatives, including AI-driven quality engineering programs and cross-functional automation strategies.
- Minimum of 4 years of experience in API testing (SOAP and REST/Microservices).
- Excellent communication skills, with the ability to articulate complex AI-driven quality strategies to both technical and non-technical stakeholders.
