Collaborate with product managers and cross-functional engineering teams to translate complex business requirements into technical solutions
Advance our ability to deliver frontend strategically — shaping SDLC practices, delivery mechanisms, and UI frameworks that scale across the platform
Mentor and guide engineers, fostering a culture of technical excellence, continuous learning, and innovation
Uphold a disciplined engineering standard — strong engineering practices, testing, accessibility, and compliance awareness — ensuring quality is built in by default
Contribute to the evolution of the team's technology strategy, evaluating emerging tools and frameworks to bring value to the technology stack
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
Proven end-to-end autonomous ownership of complex frontend deliverables involving multiple teams and stakeholders
Deep, current expertise in a modern Full- Stack technologies including Java, React, Vue, Svelte, Angular, or equivalent)— comfortable across the stack and with modular or microserices architectures
Experience working with a design system (Material, Fluent, Carbon, Radix, Bootstrap, or equivalent), partnering closely with UX and product design
Strong testing discipline (unit, integration, end-to-end) and familiarity with modern frontend build tooling (Vite, Turbopack, Webpack)
Experience designing and deploying scalable, resilient cloud-native applications on AWS, Azure, or Google Cloud
Strong problem-solving skills with the ability to manage and resolve complex technical challenges independently
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
Experience working within Financial Services or regulated technology environments
Experience partnering with design teams, translating style guides, and implementing modern web standards
Experience of engineering delivery using modern frontend SDLC frameworks, leveraging agentic practices
Ability to manage the risk and controls agenda across a technology portfolio
