Quantitative Trading Technology Engineer – Multi-Strategy Hedge Fund – London – Up to £450k TC

Quantitative Trading Technology Engineer – Multi-Strategy Hedge Fund – London – Up to £450k TC

A high-performing, multi-strategy hedge fund of around 380 people globally is in a genuine build phase across its Trading Technology platform. The firm is scaling beyond 400 people but is deliberately avoiding “mega‑fund” scale, so small engineering teams still own critical systems end-to-end and see a direct link between what they build and P&L. Around 30 hires into Technology are planned for 2026, with a particular focus on discretionary trading tech, data, and early AI‑driven tooling.

The Role – High‑Ownership Trading Tech

You will be a senior, hands-on engineer embedded with discretionary trading teams, owning key components of the trading stack rather than working in a distant central IT group. You will:

• Turn research and desk models into robust, low-latency, production services used live by PMs and traders.
• Design and own real-time and end-of-day risk, P&L, and pricing tools that directly support trade sizing and execution.
• Build and evolve scalable market and reference data pipelines, integrating vendor feeds and internal systems.
• Work directly with Portfolio Managers, quants, and Risk to shape requirements, prioritise projects, and iterate quickly on desk tools.

Example projects

• Re‑engineering a trader’s prototype Python script into a monitored microservice sitting behind the order management / blotter stack.
• Building an intraday scenario engine so PMs can stress portfolios across rates, FX, credit, and equity derivatives in seconds.
• Developing a real-time exposure dashboard with alerting that hooks into existing trading workflows.
• Collaborating with data and AI engineers on intelligent monitoring or research‑support tools (e.g. automated checks on model behaviour, smarter analytics surfaces).

Key Responsibilities

• Design, build, and maintain high-quality Python services and libraries (Pandas, NumPy; C++ exposure a plus for performance‑critical paths).
• Enhance and extend the risk modelling, pricing, and analytics suite used directly on discretionary trading desks.
• Implement solid engineering practices: testing, code review, CI/CD, monitoring, and documentation.
• Partner with front-office users to deliver new tools, debug production issues, and advocate best practices in how models and data are used in trading.

Candidate Profile

• Strong, proven programming skills in Python; experience with scientific/data libraries and production systems (not just research scripts).
• MATLAB experience required; familiarity with additional analytics tools (R, EViews) is a plus.
• Track record of owning projects end-to-end: from sitting with users to define problems, through design and implementation, to deployment and support.
• Comfortable working directly with PMs, traders, and risk in a fast-moving environment; strong communication and pragmatic problem‑solving.
• Prior front-office or risk technology experience within a bank, asset manager, or hedge fund is highly desirable.

Academic Background

• Typically a strong academic track record in a STEM discipline or related field (e.g. Maths, Computer Science, Physics, Engineering).
• Excellent results at school and university are valued, but outstanding practical skill and impact in trading or risk technology can offset a less traditional academic path.

Why now?

• You’ll be joining during a multi-year build-out of trading technology, not a maintenance phase.
• Small, focused teams mean meaningful ownership of systems that are core to how the fund trades.
• Compensation is highly competitive, with strong performance-related upside and clear visibility of the impact of your work.