About the companyOur client is a US-based quantitative hedge fund with a 15+ year track record. The team builds and runs the proprietary systems behind its research, portfolio construction, trading, execution and post-trade analysis.The strategy applies machine learning to fundamental long/short equity investing, not high-frequency trading. In practice that means correctness, reliability and clean execution matter far more than latency. This is a small, technically deep, fully remote team, so you work directly with the people who make the decisions, on systems that move real capital every week.The roleAs a Senior Trading Systems Engineer, you will help develop, optimise and scale the trading and simulation platform that executes thousands of equity trades every week. You will pair strong software engineering with a real understanding of how equity markets work, build maintainable and reusable components, and help the platform evolve as market demands change.You will work closely with a sophisticated quant team and take ownership across the trading system as a whole, not just isolated tasks.What you will doMaintain, enhance, and scale the core trading platform that communicates with various brokers through APIs and data formats.
Monitor execution of trading platform to ensure orders are placed and executed correctly
Collaborate with management and the quantitative research team to improve trading execution
Maintain and significantly enhance a trading simulation tool to reconcile simulated performance with realized trading
Design, build, and optimize systems for order management (bid/ask pricing, slippage, execution costs, P&L)
Implement robust, reusable, and scalable software solutions in Python to support trading operations
Contribute to the architecture of new features and functionalities, ensuring high performance and fault tolerance
Operate in an AWS-based environment, leveraging cloud infrastructure for computational needs
What we are looking forUniversity Degree: In computational science, engineering, computer science or similar field
Python expertise: Proven experience in building specialized, scalable systems using Python
Proper Software Engineering Practices: Enthusiastic adoption and employment of unit testing, clean and readable code
Embrace Simple, Iterative Software Design: Build the Simplest Thing that Works first; iterate later to meet future requirements
Equity Market Trading Knowledge: Knowledge of trading equity securities on US equity exchanges, including bid/ask pricing, slippage, execution frictions, and P&L estimation.
Order Management Systems (OMS): Familiarity with order routing, trade reconciliation, and algorithmic trading is a plus.
AWS Experience: Strong knowledge of AWS services and infrastructure management.
English Communication Skills: Excellent written and verbal communication in English.
Availability: Willing and able to work during the overlapping time window of 7 AM – 11 AM Eastern Time.
Market Microstructure (Plus): Experience with optimizing execution to minimize slippage and transaction costs is highly desirable.
DevOps Experience (Plus): Practical knowledge of terraform, docker and other tools used for deployment of infrastructure and code to cloud platforms.
What the first months look likeIn the first three to six months, you can expect to take ownership of a meaningful part of the platform: understand the trading architecture and the daily workflow, ship well-scoped Python improvements to reliability and observability, and lead the work on the simulation tool so that simulated and realised performance line up. From there you contribute to architecture decisions and to broker and market connectivity as the platform expands into new markets.Why this roleDirect, hands-on work across the full lifecycle of an automated trading system.
A small, high-calibre quant team, where your work has immediate business impact.
Direct access to decision-makers, with real ownership rather than narrowly scoped tickets.
A quantitative environment where engineering correctness genuinely matters.
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