Build end-to-end cloud-native, microservices-based applications using current technologies and strong engineering practices.
Apply domain modeling techniques to structure software for clarity, testability, and long-term evolution.
Develop secure, high-quality production code and review, debug, and improve code written by others.
Investigate and resolve issues promptly, ensuring root causes are addressed and problems do not recur.
Identify opportunities to eliminate or automate remediation of recurring issues to improve operational stability.
Modernize technologies and engineering patterns to keep systems current, maintainable, and scalable.
Design resilient architectures that avoid single points of failure and support reliable, scalable performance.
Lead communities of practice across Software Engineering to drive awareness and adoption of leading-edge technologies.
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
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 in software engineering concepts, or equivalent practical experience in software engineering, including system design, application development, testing, and operational support
Proficiency in back-end technologies (e.g., Java, Spring Boot, Node.js) and experience building microservices-based applications
Proficiency in front-end technologies (e.g., HTML, CSS, JavaScript, TypeScript, React, Angular)
Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies
Experience building and integrating RESTful APIs and web services, including working with JSON and WebSockets as needed
Hands-on experience designing and building scalable applications using SQL and NoSQL databases
Experience using agile development methodologies (e.g., Scrum) and applying software development life cycle practices
Proficiency in automation and continuous delivery methods, including CI/CD practices
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
Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management
Strong problem-solving, analytical, and communication skills
Ability to drive broader impact by sharing and contributing best practices
Experience in the banking domain
AWS certification
