Backend Java Software Engineer III

Job responsibilities

Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems Proactively 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 10+ years applied experience.

Hands-on practical experience in system design, application development, testing, and operational stability Demonstrable ability to code in Java Spring, Spring Boot, Microservices, Rest API Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages: MS Sql.

Sever, Oracle, Sql Overall knowledge of the Software Development Life Cycle Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud) L everages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.

g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness. 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.

Preferred qualifications, capabilities, and skills Familiarity with modern front-end technologies Exposure to cloud technologies: AWS Experience with Kafka implementations or MQ is preferred 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.