Design, develop, code, and troubleshoot with consideration of upstream and downstream systems and technical implications
Apply 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
Apply technical troubleshooting to break down solutions and solve technical problems of basic complexity
Gather, analyze, and draw conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development
Learn and apply system processes, methodologies, and skills for the development of secure, stable code and systems
Required Qualifications, Capabilities, and Skills
Formal training or certification on software engineering concepts with applied experience in delivering software solutions
Hands-on practical experience in system design, application development, testing, and operational stability
Experience developing, debugging, and maintaining code using one or more modern programming languages and database querying languages
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs
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 across the Software Development Life Cycle
Exposure to agile methodologies and practices such as CI/CD, application resiliency, and security
Preferred Qualifications, Capabilities, and Skills
Experience developing applications using Java or Python
Experience working with AWS or cloud-based services
