We see the world differently at Capstone Investment Advisors. You will, too.

Capstone is a global, alternative investment management firm operating across a broad range of derivatives-based strategies with a deep understanding of volatility. With approximately $14.6 billion of AUM and 315 employees (as of September 1, 2026, Capstone was formed in 2007 and is headquartered in New York with offices in London, Amsterdam, Tokyo, California, Stamford, Boston, and Milan.

At Capstone, we constantly aim to expand our view of how WE SEE THE WORLD DIFFERENTLY® in order to create opportunity. Our commitment to provoking the evolution of asset management provides us with a perpetual hunger for knowledge that we believe drives the improvement of our particular approach to investment. We seek to harness the complexities of global derivatives markets with disciplined strategic insight, an experienced, accomplished team and advanced technology to create sustainable value. We’ve created a particular approach to investment that we believe drives continuous improvement and opportunities for our clients, team and industry.

The Team

Capstone is looking to appoint a Senior Risk Engineer at Senior Vice President level within Risk Technology. This is a hands-on role combining software engineering, risk and financial markets, with direct exposure to the investment process. You will design and build investment-facing risk and decision-support capabilities, remaining close to the code, data and users from initial problem through to production.

This is an opportunity to build the technology behind Capstone’s Risk Intelligence strategy - turning complex risk and portfolio data into timely, actionable intelligence. You will develop tools that help Portfolio Managers and Risk Managers understand what changed, what drove it and what action to consider across stress scenarios, risk factors, margin, liquidity and portfolio analytics. The work will directly support sizing, trade expression, hedging, portfolio construction and capital allocation - helping drive better decisions, more efficient capital and more repeatable alpha.

You will work closely with Risk Managers, Portfolio Managers, Quant Research and the wider Technology, Data and AI teams. The role requires deep technical contribution, end-to-end ownership and the ability to shape outcomes through strong judgement, delivery and collaboration. It offers broad exposure across strategies and asset classes, together with the opportunity to help shape the next generation of Capstone’s Risk Technology platform.

We are building a high-performing team that values ownership, collaboration and solving difficult problems. We encourage curiosity and new ideas, alongside the discipline and reliability needed to deliver and support critical production systems.

Responsibilities and Impact

Architect, build and own production-grade components of Capstone’s Risk Technology platform, remaining close to the code, data and users and designing for performance, scalability, reliability and usability.
Build and evolve scalable cross-asset risk capabilities spanning Greeks and sensitivities, stress scenarios, VaR, P&L vectors and attribution, limits, factor analytics, margin, and exposure aggregation.
Partner directly with Portfolio Managers, Risk Managers and Quant Research to solve complex derivatives, risk and portfolio challenges, taking ideas from problem definition through to production.
Build APIs, data pipelines and interactive decision tools that help users understand what changed, what drove it and what action to consider at trade, POD, strategy and fund level.
Translate pricing and risk methodologies into scalable, explainable services, with clear treatment of model assumptions, calibration, validation and controls.
Advance Capstone’s Risk Intelligence strategy by building tools that turn research, risk analytics and AI into practical investment insight - helping Portfolio Managers and Risk Managers analyse scenarios, understand book and factor exposures, diagnose P&L and access validated analytics through natural language.