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
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 skills
Formal training or certification on software engineering concepts and 3+ years applied experience.
Strong understanding of computer science fundamentals, algorithms, and data structures.
Strong knowledge and practical experience with Java, RESTful APIs, and Microservices architectures.
Practical knowledge of CI/CD, Jenkins, and source code management tools such as Git and Bitbucket.
Practical experience with JavaScript technologies such as ReactJS or Angular, Vue.js.
Strong understanding of component based architecture using React JS, enhancing code quality with TypeScript, closures and asynchronous programming using JavaScript, and building scalable, server-side applications using NodeJS.
Hands-on professional experience in managing state within React applications, utilizing tools such as Redux and Context API to handle complex state logic and ensure seamless data flow across components.
Hands-on professional experience with automation test frameworks like Jest, Cypress and Storybook to write unit tests, component tests, contract tests, CSS techniques and frameworks.
Experience working on Cloud platform (AWS/GCP or Azure).
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
Familiarity with modern front-end technologies.
Exposure to cloud technologies - AWS, S3, EKS, IAM, Aurora Postgres, Lambda
A Government Security Clearance will be required for this position. This includes, but is not limited to:
Fingerprints
Credit Check
Employment History
US Citizen or Proof of U.S. Legal Permanent Residence for 7 years will be required.
