AI Engineer, VP

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.

GMEO (Global Markets Engineering Office) provides engineering capability, delivery discipline and scalable technology enablement for Global Markets. Global Markets AI is the specialist team responsible for AI strategy, engineering standards, reusable delivery patterns and responsible AI adoption across Global Markets. The AI Centre of Excellence (AI CoE) defines the enterprise framework, standards, reusable patterns, controls and delivery practices for the responsible adoption of AI across MUFG.

Function Aligned AI Engineers are embedded into a specific business or support function to translate functional priorities into safe, practical and measurable AI-enabled outcomes while remaining aligned to Global Markets AI and AI CoE standards. The role holder will work closely with process owners, risk and control stakeholders, technology teams, data owners, Global Markets AI and the AI CoE to identify, design, build and embed AI solutions that improve productivity, control effectiveness, employee and conduct governance, decision support and operational resilience.

MAIN PURPOSE OF THE ROLE

The Function Aligned AI Engineer is responsible for accelerating responsible AI adoption while ensuring alignment with MUFG's AI policy, data governance, technology standards, control framework, Global Markets AI engineering standards and risk appetite. The role will identify and prioritise high-value AI use cases, with clear linkage to control effectiveness, conduct governance, employee lifecycle efficiency, productivity, service improvement or risk reduction.

KEY RESPONSIBILITIES

• Prioritise and deliver AI opportunities within specific product lines, focusing on measurable productivity, quality, risk, control and service outcomes.
• Partner with leaders and process owners to assess current workflows, identify pain points, quantify benefits, define success measures and create practical delivery roadmaps.
• Build, configure and integrate AI solutions using approved enterprise platforms, tools and patterns, including generative AI, agentic workflows, RAG, prompt orchestration, workflow automation and data-driven decision support.
• Ensure solutions comply with MUFG's AI governance, model risk, information security, data privacy, records management, regulatory, compliance and operational resilience requirements.
• Design controls into AI-enabled processes, including human-in-the-loop review, explainability, validation, testing, monitoring, exception handling, evidence capture and audit trails.
• Collaborate with Global Markets AI and the AI CoE to reuse common components, contribute reusable patterns and ensure local delivery remains aligned to enterprise AI architecture and engineering standards.
• Work with technology, data, cyber, legal, risk, finance and operational teams to obtain required approvals and ensure solutions are supportable, secure and scalable.
• Deliver rapid prototypes and quick wins where appropriate, while ensuring production solutions meet engineering, governance and control expectations.
• Track benefits and adoption after implementation, including run-rate savings, productivity uplift, quality improvement, cycle-time reduction, risk reduction and user engagement.
• Provide training, documentation and practical guidance to users so AI tools are used responsibly, consistently and effectively.
• Maintain awareness of emerging AI capabilities and assess their relevance in a controlled and commercially practical manner.
• Escalate risks, issues, control gaps or conflicts of priority promptly through the functional reporting line, Global Markets AI and AI CoE governance channels.

WORK EXPERIENCE

Essential:

• AI and automation delivery – Experience designing, building or implementing AI, generative AI, automation, analytics or data-driven workflow solutions in a corporate or financial services environment.
• Solution delivery – Practical experience translating business requirements into engineered solutions, including process analysis, solution design, build, testing, deployment and adoption support.
• Regulated controls – Experience working with governance, risk, compliance, information security, data privacy or control requirements in a regulated environment.
• Engineering practice – Experience using modern software engineering practices, including version control, CI/CD, testing, documentation, peer review and release management.
• Stakeholder delivery – Experience working with business stakeholders and technology teams to deliver measurable outcomes under time, budget, policy and control constraints.

Preferred:

• Enterprise GenAI – Experience implementing generative AI or agentic AI solutions in enterprise environments.
• Knowledge workflows – Experience with retrieval-augmented generation, vector search, knowledge management, document intelligence or workflow orchestration.
• Regulated industry – Experience in banking, capital markets, financial services or another highly regulated industry.
• Platforms – Experience with cloud platforms, data platforms and enterprise integration patterns.

SKILLS AND EXPERIENCE

Essential:

• Generative AI – Strong understanding of generative AI concepts, including prompt design, model selection, RAG, embeddings, evaluation, hallucination risk, guardrails and responsible AI controls.
• Agentic workflows – Ability to design and implement agentic or semi-agentic workflows with appropriate human oversight, logging, validation and exception handling.
• Python – Strong Python development skills and ability to build maintainable, tested and documented code.
• SQL and databases – SQL and database experience, including data extraction, transformation, validation and integration.
• APIs and integration – Experience with APIs, workflow integration and secure system-to-system connectivity.
• Cloud architecture – Practical understanding of cloud-based programming and architecture, particularly Azure; AWS experience is also beneficial.
• Data platforms – Experience with enterprise data platforms such as Snowflake or equivalent.
• AI-assisted engineering – Use of AI-assisted engineering tools such as GitHub Copilot, Claude Code or equivalent agentic coding harnesses, with appropriate review and control of generated outputs.
• CI/CD – Use of industry-standard CI/CD and software delivery tools such as Git, TeamCity, deployment automation and issue-tracking platforms.
• Secure development – Understanding of secure software development, data classification, access control, secrets management and auditability.
• Testing and acceptance – Ability to define test plans and acceptance criteria for AI-enabled solutions, including functional testing, regression testing, model and prompt evaluation, and control testing.
• Communication – Ability to communicate technical concepts clearly to non-technical stakeholders and convert functional problems into practical solution designs.

Preferred:

• AI platforms – Experience with AI orchestration frameworks, model evaluation tooling, vector databases, document processing, knowledge retrieval or workflow automation platforms.
• AI governance – Familiarity with model risk management, AI governance, EU AI Act concepts, data privacy and regulatory expectations for AI in financial services.
• Benefits realisation – Understanding of process improvement methods and benefits realisation.