Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
Adds to team culture of diversity, opportunity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years hands on Software Development Life Cycle experience
Experience implementing solutions using Java, SQL, UI frameworks, Design patterns, microservices, Cloud native architecture, Angular/React, RESTful APIs for enterprise-scale applications.
Experience with SQL performance tuning, JDBC, and ORM frameworks (Hibernate/JPA)
Strong experience in various SQL and NoSQL datastores including Oracle, MongoDB
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Proficiency in unit testing frameworks such as JUnit and Mockito for ensuring code quality.
Deep knowledge of messaging platforms such as Apache Kafka
Preferred qualifications, capabilities, and skills
Familiarity with DevOps practices, containerization and orchestration
Exposure to AI systems such as Copilot, Claude
Exposure to AWS technology stack
