Lead Java Engineer - Equities Algo Trading Platform

Next Frontier Capital; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

JPMorgan Chase is seeking a Lead Software Engineer within the Equities Trading Technology Organization. You will be a core technical contributor responsible for building and maintaining a market-leading algo execution platform for global markets.

Expect collaboration with quants, traders, and technologists across a globally distributed team. The role spans engine infrastructure, quantitative models, trading signals introduction, and performance tuning to improve strategy behavior.

Qualifications

• Formal training or certification in software engineering concepts with proficient advanced experience in Java.
• Proficiency in low latency, real-time, scalable trading systems.
• Experience with high throughput messaging APIs and middleware products.
• Experience with algorithmic trading, including systematic trading.

Responsibilities

• Design and develop algo trading strategies and execution platform.
• Design and develop simulation environment and maintain automated testing of strategies.
• Enhance existing strategies by reviewing analytics and evolving models/signals.
• Support the desk by investigating cases to interpret strategy behavior and address issues.
• Develop scalable real-time processing solutions using agile methodologies.
• Automate remediation of recurring issues to improve operational stability.

Skills

Java proficiency

Low latency systems

Messaging APIs

Algorithmic trading

Education

CS / Computer Engineering / Mathematics degree

Tools

FIX protocol

Market Data

OMS

Job description

JPMorgan Chase is seeking a Lead Software Engineer within the Equities Trading Technology Organization. You will be a core technical contributor responsible for building and maintaining a market-leading algo execution platform for global markets.

Expect collaboration with quants, traders, and technologists across a globally distributed team. The role spans engine infrastructure, quantitative models, trading signals introduction, and performance tuning to improve strategy behavior.