VP, Quant Developer - Risk Analytics

the opportunity to work closely with other risk analytics teams, including Market Risk , Credit Risk , and RegIM , to design and operate AI-powered systems that automate complex risk workflows and support regulatory submissions. The ideal candidate brings equal depth in Agentic Coding and financial risk domain knowledge , with hands-on experience structuring agentic workflows, validating AI-generated output, and architecting end-to-end systems in environments similar to Claude Code.

- Design and implement end-to-end agentic workflows that enable autonomous planning, multi-step execution, and tool use across risk analytics and regulatory submission processes.

- Architect and own the full system design of AI-powered risk platforms, including data flow, tool integration, orchestration layer, and production deployment.

- Build and maintain validation frameworks and testing pipelines to ensure the correctness and reliability of AI-generated code and analytical outputs in a financial risk context.

- Develop and integrate LLM-powered developer tooling - including CLI-based agents and code generation/review pipelines - to accelerate risk analytics delivery.

- Collaborate with Market Risk, Credit Risk, and RegIM teams to translate complex domain requirements into robust, automated Python solutions.

- Develop scalable, reusable Python libraries and contribute to a robust CI/CD environment through testing, peer review, and version control.

- Facilitate efficient data processing, integration, and reporting pipelines to streamline regulatory submissions and internal analytics.

- Education: Master's degree in Financial Engineering, Mathematics, Computer Science, or a related quantitative field preferred; Bachelor's considered with exceptional experience.

- Experience: At least 5 years of professional experience in Python backend development for financial applications.

- Demonstrated experience designing and maintaining multi-step agentic workflows, orchestration logic, branching execution, and tool use - not limited to simple LLM API calls.

- Practical experience building validation frameworks or testing pipelines to verify AI-generated outputs in a professional setting; concrete examples required.

- Hands-on experience with LLM-powered developer tooling or systems similar to Claude Code, including CLI-based AI agents or LLM-assisted code generation and review pipelines.

- Proven ability to own full system architecture for agentic platforms, covering data flow, tool integration, orchestration, and deployment.

- Strong knowledge of financial risk domains, specifically Market Risk (VaR, ES, Greeks, stress testing, FRTB) and Credit Risk (PD/LGD/EAD, CECL, CCAR, SA-CCR).

- Demonstrated ability to develop scalable, reusable Python libraries.

- Knowledge of RegIM / SIMM (Regulatory Initial Margin, ISDA SIMM methodology, IM regulatory submissions) is highly desirable.

- Experience with portfolio analytics across multiple asset classes, including derivatives pricing and factor models.

- Proficiency with DevOps tooling: Docker, Kubernetes, cloud platforms (Azure/AWS), and CI/CD pipelines.

- Familiarity with graphical user interface (GUI) development in Python.

- Ability to handle large datasets and implement efficient processing algorithms.

Primary Location Full Time Salary Range of $175,000 - $200,000.