• Drives adoption and governance of approved AI-assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test acceleration, release readiness, incident/root-cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain.

• Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI-assisted development and automation capabilities, to improve the value realized by automation at scale.

* Software development with Java and associated frameworks such as Spring, Spring Web, Spring Boot, Spring Security

* Use of relational databases, SQL, and data integrity constraints

* Use of industry wide technology trends and best practices

* practice  following Agile methodology

* Working in large, collaborative teams to achieve organizational goals, and passionate about building an innovative culture

•  Formal training or certification on software engineering concepts and 5+ years applied experience

• Hands-on practical experience delivering system design, application development, testing, and operational stability

• Advanced in one or more programming language Java

• Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.