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.
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.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience.
Hands-on practical experience in system design, overall knowledge of SDLC, application development, testing, and operational stability.
Full-stack development with Java/Spring Boot and React — building and maintaining secure backend services and modern web UIs in an enterprise environment.
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages - Java / Spring Boot.
Experience with React.
Cloud-native engineering on AWS — designing, deploying, and operating scalable services (including reliability, security, and cost-aware patterns).
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.
Operational excellence (CI/CD, resiliency, security, automation) — strong SDLC practices, automating recurring remediation, and improving stability/observability of production systems.
System design & architecture leadership — producing architecture/design artifacts, evaluating technical designs, and leading modules/technical decision-making across teams.
Preferred qualifications, capabilities and skills
Strong architecture/design review skills; able to align solutions to existing platforms and standards.
Experience building cloud-native solutions on Amazon Web Services.
Module/workstream leadership and mentoring experience within agile teams.
Experience with data integration patterns and event-driven architectures (e.g., Kafka or similar messaging/streaming technologies).
Responsible use of enterprise-authorized AI development tools, with strong validation discipline (tests/peer review).
Knowledge on observability practices (logs/metrics/traces, dashboards, alerting).
Financial services knowledge, with an understanding of how technology enables Commercial & Investment Bank products and client experiences.
