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.
Identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Contributes to software engineering communities of practice and events that explore new and emerging 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 3+ years applied experience
Hands-on practical experience in system design, application development, testing and operational stability
Proficient in coding in Java & React, JavaScript languages
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
Overall knowledge of the Software Development Life Cycle
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.
Understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Preferred qualifications, capabilities, and skills
Experience with AWS Cloud
