Execute software solutions across design, development, and technical troubleshooting to build innovative, production-ready applications
Create secure, high-quality production code and maintain algorithms that operate synchronously with appropriate systems
Produce architecture and design artifacts for complex applications, ensuring all design constraints and standards are met
Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets to inform technical decisions
Identify hidden problems and patterns in data to drive improvements in coding hygiene and overall system architecture
Contribute to software engineering communities of practice and participate in events exploring new and emerging technologies
Foster a team culture of diversity, equity, inclusion, and respect through active collaboration and engagement
Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
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 ski
lls
Formal training or certification on software engineering concepts and proficient applied experience
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-scale environment using modern programming languages and database querying languages
Hands-on experience in server-side Core Java, XML, JSON, J2EE programming, Spring Framework, and associated design techniques
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Experience developing web applications and REST APIs, with exposure to relational databases (Oracle/Sybase) or non-relational databases (MongoDB)
Working knowledge of version control using Git, continuous integration tools such as Jenkins, and automation testing tools such as Selenium, Cucumber, Flyway, or Concordion
Knowledge of Linux, shell scripting, and application services including Apache, Tomcat, and Spring Boot
Experience with user interface technologies (Angular, TypeScript, React) and user interface testing tools (Jasmine, Karma, Jest)
Working experience with cloud-native platforms (AWS, Kubernetes, or private cloud environments)
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
Preferred qualifications, capabilities, and skills
Familiarity with modern front-end technologies and evolving user interface frameworks
Exposure to cloud technologies and cloud-native development patterns
Knowledge of industry-wide technology trends and best practices across technical disciplines such as artificial intelligence, machine learning, and mobile
Ability to work effectively within large, collaborative teams to achieve shared organizational goals
Passion for building an innovative, inclusive engineering culture
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