Proactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture
Write secure and high-quality code in Java, Angular, RESTful APIs, and SOAP, applying knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation
Apply advanced technical troubleshooting to break down and resolve complex technical problems, applying system processes, methodologies, and skills for the development of secure, stable code and systems
Mentor and guide junior engineers, fostering a culture of technical excellence, collaboration, and continuous improvement
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
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
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and advanced applied experience
Hands-on practical experience in system design, application development, testing, and operational stability
Proficiency in coding in one or more programming languages
Experience developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
Strong understanding of the Software Development Life Cycle
Experience writing well-tested, secure, and readable code in Java, UI frameworks such as Angular, RESTful APIs, and SOAP
Experience with RESTful web service development using Spring Boot, Hibernate, or a similar framework
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices
Preferred qualifications, capabilities, and skills
Hands-on experience with cloud-native architectures and infrastructure
Practical understanding of containerized application development and deployment using Docker, Kubernetes, Kafka, and AWS
Experience with component-based web UI frameworks such as ReactJS, Angular, or Vue.js, and knowledge of relational databases and SQL, especially Oracle
Experience working as part of an agile, user-centric product team
