Summary
What you’ll impact
The Vice President Full Stack Engineer will design and develop Python-based risk integration solutions, build end-to-end risk workflows, and ensure performance and reliability of data pipelines. The role also involves implementing CI/CD pipelines, test automation, and applying AI/agentic workflow concepts to enhance automation and operational efficiency.
Responsibilities
What you'll do
- Design and develop Python-based solutions for risk integration, orchestration, and data processing
- Build and manage end-to-end risk workflows including trade ingestion, compute, aggregation, and reporting
- Develop and maintain test harness, regression frameworks, and quality engineering standards
- Optimize data pipelines and compute frameworks to ensure performance, scalability, and reliability
- Implement CI/CD pipelines and automate engineering tasks using Python, Shell, and PowerShell
- Apply AI and agentic workflow concepts to improve automation and operational efficiency
Requirements
What you’ll bring
- Bachelor's or master's degree in computer science, Engineering, or related discipline
- Strong hands-on experience in Python,PySpark with Java
- Experience with SQL Server, Oracle, and MongoDB
- Proficiency in Linux (Shell scripting) and Windows (PowerShell)
- Experience in CI/CD, integration, workflow orchestration, and test automation
- Strong knowledge of core financial risk concepts and developer workflows, including market risk and counterparty risk, VaR/SVaR, sensitivities, stress testing, PnL, pricing and exposure measures across fixed income, cash equity, FX, and derivatives.
- Strong understanding of fixed income instruments such as government bonds, corporate bonds, municipal bonds, callable bonds, asset-backed securities, and MBS, as well as cash equities.
- Experience working with financial risk platforms and integrations, including Quant Model, with expertise in upstream source onboarding, market data discovery and sourcing, security master and reference data onboarding, price ingestion and validation, data quality controls, reconciliation, workflow orchestration, issue triage, and support for audit, controls, and production resiliency.
- Strong understanding of solution architecture and design, with emphasis on implementing secure, controlled environments incorporating IT controls, including vulnerability management, security best practices, and compliance frameworks.
- Exposure to AI/ML, agentic workflows, and automation-first engineering mindset