VP – Data Products and AI Enablement

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.

The selected colleague will work at an MUFG office or client sites four days per week and work remotely one day. A member of our recruitment team will provide more details.

Vice President
- Data Products& AI Enablement

Job Summary The Vice President
- Data Products & AI Enablement is a hands-on engineering role responsible for designing, building, and scaling the bank’s data and AI engineering platforms. The role focuses on high-performance data infrastructure, distributed systems, AI/ML platforms, data pipelines, semantic retrieval, and production-grade AI services that enable enterprise analytics and intelligent applications across the bank. The ideal candidate combines strong software engineering fundamentals with deep expertise in data infrastructure, distributed systems, cloud platforms, and emerging AI technologies.

Major Responsibilities Design and develop scalable backend data and AI platforms supporting commercial banking, risk, finance, operations, and enterprise data use cases.

Build production-grade AI infrastructure including vector search, embeddings, RAG pipelines, LLM integrations, AI agents, semantic retrieval, and intelligent data services.

Develop high-volume data pipelines and distributed processing frameworks using Python, SQL, Kafka, Airflow, Spark, and cloud-native technologies.

Optimize data storage, retrieval, indexing, and compute performance across large-scale structured, unstructured, and vector datasets.

Develop and operationalize AI/ML workloads across cloud infrastructure, including model serving, inference, retrieval, evaluation, monitoring, and lifecycle management.

Partner with data scientists, AI engineers, product managers, architects, cybersecurity, risk, and business teams to translate complex requirements into scalable technical solutions.

Qualifications

Required8+ years of progressive software, backend, platform, or data engineering experience, including enterprise-scale distributed systems and production data platforms.

Knowledge of data security, governance, high availability, disaster recovery, observability, and performance optimization.

Strong communication, stakeholder management, problem-solving, and technical leadership skills.

Preferred Advanced degree or relevant cloud, data engineering, Kubernetes, or AI/ML certifications.

Experience delivering technology solutions in financial services or another highly regulated industry.

Experience partnering with cybersecurity, data governance, model risk, architecture, and control functions.

Core Expertise AI/LLM Engineering | Agentic AI | RAG and Vector Search | Data Engineering | Distributed Systems | Python and SQL | Kafka | Airflow | Spark | Kubernetes | AWS/Cloud | APIs and Microservices | AI/ML Infrastructure | Data Security and Governance | High Availability | CI/CD | Financial Services

Education:

Bachelor's degree in Computer Science or a closely-related discipline, or an equivalent combination of…