Assistant Vice President

Do you want your voice heard and your actions to count?

Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world’s leading financial groups. Across the globe, we’re 150,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.

With a vision to be the world’s most trusted financial group, it’s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career.

Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.

Job Profile

We are seeking an experienced Assistant Vice President (AVP) Full Stack AI Engineer to lead the design, development, modernization and support of business-critical TPS applications. The role provides hands-on technical leadership across full stack application engineering, infrastructure and platform changes, production readiness and AI-enabled software engineering practices. The successful candidate will deliver secure, scalable, resilient and maintainable solutions in a regulated financial services environment, while guiding engineers and collaborating with business, architecture, infrastructure, security and operations stakeholders.

Key Technical Skills

Enterprise AI coding assistants, GitHub Copilot or equivalent approved tools, and AI-enabled SDLC practices

Java and J2EE

ReactJS, HTML5, CSS3 and JSX

JavaScript fundamentals and ES6+

Node.js, npm and Redux

Git and modern source-control practices

RESTful APIs, distributed systems and multi-tier architectures

Relational databases and enterprise integration patterns

CI/CD, DevSecOps, static and dynamic code analysis, and automated testing

AWS, container platforms, Kubernetes and Infrastructure as Code

Monitoring, observability, resilience and disaster-recovery practices

Additional Requirements

Ability to work effectively in a dynamic, fast-changing environment and manage competing priorities.

Strong collaboration skills and the ability to influence cross-functional and geographically distributed teams.

Excellent verbal and written communication skills, including the ability to present technical concepts to senior technical and non-technical stakeholders.

Strong ownership, judgement, structured problem-solving and delivery discipline.

Willingness to support planned production deployments, including occasional weekend activities when required.

Responsibilities for This Role

AI-Enabled SDLC: Identify and implement approved AI use cases across requirements analysis, code generation, code review, test generation, documentation, defect analysis and engineering knowledge management.

Responsible AI Governance: Ensure AI-generated outputs are subject to appropriate human review and controls for correctness, security, privacy, intellectual property, regulatory compliance, auditability and traceability.

AI Adoption and Measurement: Guide onboarding and adoption of enterprise-approved AI coding assistants and engineering agents, and measure outcomes using agreed indicators for adoption, quality, rework, testing efficiency and delivery flow.

Application and System Development: Lead end-to-end design, development, modernization, testing, release and support of full stack application solutions that integrate with enterprise applications and legacy systems.

Technical Design and Engineering Governance: Own solution design, conduct design and code reviews, guide technology choices, and establish standards for clean code, reusable components, API design, automated testing, security and documentation.

Infrastructure and Platform Changes: Lead and coordinate changes covering hosting, middleware, databases, network connectivity, certificates, compute, storage, containers, cloud services and environment configuration.

Change and Production Readiness: Own infrastructure impact assessment, dependency analysis, implementation planning, testing, rollback planning, release coordination and post-implementation validation in alignment with enterprise change controls.

Platform Modernization: Drive cloud adoption, containerization, environment automation, Infrastructure as Code, observability, capacity planning, resilience, disaster recovery and performance improvements.

Stakeholder Collaboration: Partner with product owners, business analysts, architects, infrastructure, cyber security, service management and operations teams to refine scope, manage dependencies and resolve risks.

Technical Leadership: Mentor engineers, improve team capability, promote knowledge sharing and foster a culture of ownership, collaboration and continuous improvement.

Operational Excellence: Lead root-cause analysis for complex incidents and drive corrective and preventive actions that improve stability and supportability.

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 equival