Senior Trading System Engineer — Low-Latency Python

Ainnocence; Hong Kong; On-site; HKD 900,000 - 1,500,000; Full time

Job summary

Ainnocence is seeking a Trading System Engineer to own the production trading system for a global multi-asset Quant fund. You will work with an in-house Python stack to turn signals into filled orders via Interactive Brokers, running 24/5 across Asia, Europe and the US.

The role combines keeping the system running with real improvements: designing execution logic, reducing costs, and extending the architecture for new strategies and asset classes.

Qualifications

• 4+ years of production Python in a trading or low-latency setting.
• Hands-on Interactive Brokers API experience in live trading.
• Ownership of an execution or latency-sensitive system.
• Profiling and performance work in Python; know asyncio and related tools.
• Knowledge of market microstructure and fill quality reasoning.
• Linux, Git, CI/CD; time-series data stores; messaging systems.

Responsibilities

• Build and optimize execution algorithms with order placement logic.
• Reduce transaction costs via a TCA feedback loop and measurable slippage.
• Profile hot paths; address latency, serialization, and bottlenecks.
• Refactor and extend codebase for new assets and strategies.
• Move strategies from backtest to live with behavioural parity.
• Harden IB layer: session management, reconnection, idempotent orders.
• Own order lifecycle: routing, state machine, end-of-day handling.
• Perform pre-trade risk checks and post-trade reconciliation.
• Establish observability: monitoring, runbooks, on-call coverage.

Skills

Python

Low-latency

IB API

Performance profiling

Linux

Git CI/CD

Tools

PostgreSQL

Redis

Kafka

ZeroMQ

Job description

Ainnocence is seeking a Trading System Engineer to own the production trading system for a global multi-asset Quant fund. You will work with an in-house Python stack to turn signals into filled orders via Interactive Brokers, running 24/5 across Asia, Europe and the US.

The role combines keeping the system running with real improvements: designing execution logic, reducing costs, and extending the architecture for new strategies and asset classes.