Job Description
SMBC Group is a top-tier global financial group. Headquartered in Tokyo and with a 400-year history, SMBC Group offers a diverse range of financial services, including banking, leasing, securities, credit cards, and consumer finance. The Group has more than 130 offices and 80,000 employees worldwide in nearly 40 countries. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMFG’s shares trade on the Tokyo, Nagoya, and New York (NYSE: SMFG) stock exchanges.
In the Americas, SMBC Group has a presence in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru. Backed by the capital strength of SMBC Group and the value of its relationships in Asia, the Group offers a range of commercial and investment banking services to its corporate, institutional, and municipal clients. It connects a diverse client base to local markets and the organization’s extensive global network. The Group’s operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., SMBC MANUBANK, JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd.
Join our Risk Technology team as a Senior Risk Developer (VP) and help build the platforms that power enterprise risk analytics, automation, and decision-making. In this role, you will design scalable data products, develop AI and machine learning solutions, and deliver user-facing applications that support risk management across the organization. You will work closely with Risk, Data Science, Product, and Engineering teams to translate business needs into secure, reliable, and auditable technology solutions. This position offers the opportunity to influence enterprise-scale risk platforms from design through production support.
PRINCIPAL DUTIES AND RESPONSIBILITIES
- Design, build, and maintain risk data platforms, pipelines, and curated datasets using Azure Databricks to support enterprise risk management and reporting.
- Develop and optimize data ingestion, transformation, storage, and retrieval solutions using Python and SQL, with a focus on scalability, reliability, and auditability.
- Build, deploy, monitor, and maintain AI and machine learning models for risk analytics, using MLflow for experimentation, version control, lineage, and governance.
- Design and implement AI-powered workflows and prompt-based solutions that improve risk analysis, monitoring, validation, and decision support.
- Implement CI/CD pipelines and automated deployment processes for data products, models, and applications, ensuring controlled releases and production stability.
- Develop user-facing risk applications and dashboards, including React-based interfaces that integrate with data services, models, and backend APIs.
- Partner with Risk, Data Science, Product, and Engineering teams to gather requirements, define solution architecture, and deliver technology solutions that meet business objectives.
- Lead technical delivery efforts, promote engineering quality standards, and provide clear communication on architecture decisions, risks, and delivery progress.
POSITION SPECIFICATIONS
- 7+ years of software engineering, data engineering, or risk technology experience within financial services.
- Experience leading complex technology initiatives and delivering solutions in Agile development environments.
- Experience building and operating production AI and machine learning solutions across the full model lifecycle.
- Advanced expertise with Azure Databricks, including large-scale data processing and data pipeline development.
- Strong SQL skills, including SQL Server, T-SQL, and stored procedure development.
- Strong Python development experience for data engineering, analytics, and application development.
- Working knowledge of Oracle and PL/SQL.
- Hands-on experience with Azure services, including Azure Data Lake Storage, Azure Functions, Azure Event Grid, Azure Service Bus, Azure Monitor, and Azure Log Analytics.
- Experience implementing CI/CD practices using Azure DevOps or comparable enterprise tooling.
- Experience using Databricks MLflow for model tracking, experimentation, deployment, and governance.
- Experience implementing AI-assisted workflows, generative AI solutions, or prompt-based applications in production environments.
- Understanding of model governance, monitoring, and operational controls.
- Experience developing modern web applications using React and integrating front-end applications with APIs, backend services, and data platforms.
- Ability to communicate technical concepts clearly to both technical and non-technical audiences.
- Experience working across Risk, Engineering, Data Science, and Product teams to deliver business outcomes.
SMBC’s employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well as, from an SMBC office. SMBC requires that employees live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during their interview process. Hybrid work may not be permitted for certain roles, including, for example, certain FINRA-registered roles for which in-office attendance for the entire workweek is required.
SMBC provides reasonable accommodations during candidacy for applicants with disabilities consistent with applicable federal, state, and local law. If you need a reasonable accommodation during the application process, please let us know at accommodations@smbcgroup.com.
