In this role, you’ll make an impact in the following ways:
- Experience developing applications for market risk, credit risk, liquidity risk, stress testing, forecasting, or regulatory reporting.
- Understanding of mathematical and financial models, model implementation, validation controls, and data-quality requirements.
- Experience with real-time or near-real-time data ingestion, high-volume processing, and highly available enterprise platforms.
- Exposure to AI-assisted development tools and the responsible use of AI across design, coding, testing, documentation, and production support.
- Experience presenting technical strategy, delivery status, risks, and trade-offs to senior stakeholders.
- Strategic thinking combined with a strong bias for execution.
- Sound judgment in balancing speed, quality, security, risk, and long-term maintainability.
- Ability to influence without authority and build alignment across diverse teams.
- Commitment to mentoring engineers, improving engineering maturity, and creating an inclusive, collaborative team environment.
- Lead the architecture, design, development, testing, deployment, and support of end-to-end full-stack applications.
- Build responsive user experiences, robust APIs, scalable backend services, and reliable data integrations using modern engineering practices.
- Translate business, product, risk, and regulatory requirements into maintainable technical designs and delivery plans.
- Develop and integrate workflows for financial forecasting, stress testing, scenario analysis, sensitivity analysis, attribution, and risk reporting.
- Collaborate with quantitative and risk teams to productionize analytical and machine-learning models developed in Python, R, or related technologies.
- Establish engineering standards for code quality, security, testing, observability, performance, and resiliency.
- Drive code reviews, automated testing, CI/CD adoption, release governance, and production-readiness reviews.
- Troubleshoot complex production issues, optimize application performance, and ensure service-level expectations are met.
- Provide technical mentorship, influence architecture decisions, and foster a culture of ownership and continuous improvement.
Manage priorities, dependencies, risks, and delivery commitments across cross-functional teams and stakeholders.
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To be successful in this role, we’re seeking the following:
Bachelor’s or master’s degree in Computer Science, Engineering, Mathematics, Data Science, Financial Engineering, or a related quantitative discipline.
Typically 4-9 years of software engineering experience, including significant ownership of enterprise application delivery; financial-services experience is strongly preferred.
Demonstrated ability to lead technical design and delivery while remaining hands-on with development and problem solving.
Strong written and verbal communication skills, with the ability to explain complex technical concepts to engineering and business stakeholders.
Experience working in Agile delivery models and coordinating work across product, engineering, risk, operations, and control functions.
