1 month ago
Base Salary
$175k - $200k/yr
Responsibilities
- Design and implement autonomous, multi-step agentic workflows with planning, branching execution, and tool use for risk analytics and regulatory submissions.
- Own the architecture and production deployment of AI-powered risk platforms, including data flow, tool integration, and orchestration layers.
- Build validation frameworks and testing pipelines to verify AI-generated code and analytical outputs.
- Develop LLM-powered developer tooling, including CLI agents and code-generation and review pipelines.
- Translate Market Risk, Credit Risk, and RegIM requirements into robust Python solutions.
- Develop scalable Python libraries and contribute to testing, peer review, version control, and CI/CD practices.
- Build efficient data processing, integration, and reporting pipelines for regulatory submissions and internal analytics.
Requirements
- A master's degree in Financial Engineering, Mathematics, Computer Science, or a related quantitative field is preferred; a bachelor's degree may be considered with exceptional experience.
- At least 5 years of professional Python backend development experience for financial applications.
- Demonstrated experience designing and maintaining multi-step agentic workflows, orchestration logic, branching execution, and tool use beyond simple LLM API calls.
- Professional experience building validation frameworks or testing pipelines for AI-generated outputs, with 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.
- Experience owning full system architecture for agentic platforms, including data flow, tool integration, orchestration, and deployment.
- Strong knowledge of Market Risk concepts including VaR, ES, Greeks, stress testing, and FRTB, and Credit Risk concepts including PD/LGD/EAD, CECL, CCAR, and SA-CCR.
- Ability to develop scalable, reusable Python libraries.
- Knowledge of RegIM/SIMM and experience with portfolio analytics, derivatives pricing, factor models, large datasets, or efficient processing algorithms are preferred.
- Proficiency with Docker, Kubernetes, Azure or AWS, and related DevOps tooling is preferred.
- Familiarity with Python GUI development is preferred.
Benefits
- Full-time position.
- Primary location is specified in the posting.
- Base salary range is $175,000-$200,000.
Tech Stack
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