Lead BI and AI/ML 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.

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.

Job Summary:

The Data Platform Engineering team is embarking on a transformative journey to define, enable, and drive our data strategy. We aim to engage with partners across technology, data, business, and operations to develop and deliver business outcomes.

Our team is seeking an experienced and dynamic individual to join as Lead Data AI (AI/ML ops) and BI (Business Intelligence & Data consumption), VP  to be an SME & Leader, into the Enterprise Data & Data Capabilities group. (aka: EDDC)

• This visible and impactful position requires engaging with variety of stakeholders and technologists. This role will help define Cloud Data-Ops, AI-ML solutions and Capabilities in line with the overall data strategy of technology and business
• This role requires a deep understanding of data management strategies, best practices, and innovative technologies, including data virtualization, data pipelines, data consumption, and data reporting and AI/ML ecosystems.
• With AI/ML technologies playing a critical role in content creation, personalization, and audience engagement, this role expertise will be instrumental in optimizing resource utilization, managing budgets, and implementing innovative cost-saving strategies.
• Act as proactive leader who understands the interplay between development, security, and operations in AI/ML workflows.

Roles and Responsibilities:

• Provide leadership in helping the EDDC group with AWS operational aspects - IAM roles, Policies and Permissions, security guardrails.
• Guide and pursuit the aspects related to reliability, scalability, and performance of MUFG’s Cloud infrastructure, platforms, and applications
• Extend help in cloud architecture & migration as well as setting up AWS AI/ML Solutions (with a focus on AWS Bedrock, SageMaker, Amazon Q)
• Work with cutting-edge ML models and AI-driven applications, focusing on improving (RAG) systems and evolving MCP practices to develop scalable solutions.
• Utilize Pinecone or Singlestore for scalable vector search solutions, enhancing the performance of search/retrieval systems with fast, scalable vector search techniques.
• Manage large datasets, applying best practices in machine learning to ensure robust model training, validation, and deployment pipelines.
• Design and implement robust CI/CD pipelines for AI/ML model development, testing, and deployment, ensuring minimal downtime and maximum efficiency. 
• Automate model versioning, retraining, and deployment workflows to streamline the AI/ML lifecycle. Implement monitoring and alerting mechanisms to ensure the continuous health of AI/ML pipelines. 
• Maintain active Interface with Cloud-Engineering and Cloud SecOps in smooth resource provisioning and its usage for the data services group applications.
• Assist in evolving DevOps & Automation practices (Terraform, CI/CD etc.) Drive the adoption of (IaC) to streamline operations, minimize manual work, add scalability.
• Evolve practices to adhere to MUFG Security & Compliance (Secure by Design, Zero-Trust, IAM, Guardrails, KMS, SCPs)
• Develop technical documentation, user guides, and presentations for diverse teams
• Continuously evaluate system design and usage to identify opportunities for cost optimization, ensuring cloud infrastructure efficiency.
• Collaborate with cross-functional teams, working closely with Data Scientists, Product Managers, and Backend Engineers to deploy AI solutions into production.
• Conduct ongoing research to stay updated with advancements in generative AI, machine learning, and deep learning, integrating innovative solutions into products and services.
• Guide and aid business intelligence and reporting group