Role Qualifications (Skills, Previous Roles)
• Strong hands-on experience across client-side and server-side development, with the ability to work across multiple technologies.
• Proven experience designing and delivering distributed, multi-tier enterprise applications and integrations.
• Experience leading technical delivery, engineering workstreams, infrastructure changes or platform-modernization initiatives.
• Experience collaborating across Architecture, Infrastructure, Cyber Security, Service Management and Operations functions.
• Experience implementing AI-assisted engineering capabilities in an enterprise environment, with appropriate governance and human oversight.
• Strong understanding of object-oriented analysis, design principles, design patterns, algorithms and database concepts.
• End-to-end SDLC experience, preferably within financial services or another regulated industry.
• Strong organizational, analytical, problem-solving and time-management skills, with the ability to meet delivery commitments.
• Knowledge of application-security vulnerabilities and secure engineering practices.
• Hands-on experience working within Agile and / or Scrum delivery teams.
Essential Skills and Experience
• Minimum 10 years of software engineering experience, including substantial hands-on full stack development and technical leadership responsibilities.
• Strong practical experience with Java / J2EE and modern front-end technologies including ReactJS, HTML, CSS, JSX and JavaScript ES6+.
• Thorough understanding of React core principles, component design, state-management workflows such as Redux, and RESTful API integration.
• Experience planning and delivering enterprise infrastructure and platform changes, including impact assessment, dependency management, implementation, rollback and validation.
• Working knowledge of cloud and on-premises infrastructure, middleware, networking, databases, certificates, containers, Kubernetes, Infrastructure as Code, monitoring, resilience and disaster recovery.
• Experience with CI/CD pipelines, source control, automated testing, code-quality tooling, security scanning and release automation.
• Practical experience implementing enterprise AI capabilities within the SDLC, such as AI-assisted requirements analysis, coding, code review, testing, documentation or engineering knowledge management.
• Understanding of Responsible AI, data protection, secure usage, human validation, auditability and governance requirements for AI-assisted software engineering.
• Experience mentoring engineers, conducting technical reviews and influencing quality and engineering practices across teams.
• Strong analytical ability, attention to detail and structured thinking.
• Bachelor’s degree in computer science, Engineering, Information Technology or a related discipline, or equivalent practical experience.