Decision Engine Developer

Capital Bank, N.A. is a publicly traded company offering commercial and consumer banking services. The Decision Engine Developer will design, build, and test eligibility and decision strategies within a low-code decision engine platform, collaborating with business and technical teams to ensure effective implementation and optimization of decisioning processes.

Responsibilities:

• Translate business requirements into decision engine rules and workflows
• Build and maintain rulesets within the decision platform
• Implement automated processes to improve efficiency and consistency
• Perform comprehensive unit, integration, and regression testing
• Validate that decision outcomes align with expected results and business intent
• Troubleshoot and debug issues within rules, data flows, and integrations
• Support system performance monitoring and issue resolution
• Assist in identifying risks, gaps, and improvement opportunities within strategies
• Contribute to performance tracking, reporting, and ongoing optimization efforts
• Partner with business stakeholders to understand detailed requirements and expected outcomes
• Work with technical teams to apply platform best practices and ensure proper implementation
• Communicate progress, issues, and results clearly to stakeholders
• Manage assigned deliverables and contribute to project timelines
• Ensure work is completed accurately, on time, and in alignment with requirements
• Support releases and deployments, including validation and post-implementation checks
• Provide guidance to junior team members on development and testing best practices
• Contribute to documentation, standards, and reusable components

Requirements:

• 3-5 years risk management strategy implementation experience in a FinTech / banking environment
• Bachelor's degree in computer science, business administration, mathematics, engineering, or related quantitative discipline
• 3-5 years low-code decision engine system experience (GDS Link, Provenir, Decisions, Oscilar, etc.)
• Object-oriented programming expertise
• Experience implementing JavaScript in a back-end environment (e.g. NodeJS)
• Understanding of credit risk business domain
• Master's degree in business, mathematics, engineering, or related discipline
• Experience with implementing credit and fraud risk models (R, Python, SAS)
• Data analysis experience (SQL, Excel, PowerBI)