Software Engineer – Trading Systems & Data Infrastructure

Software Engineer – Trading Platform & Data Infrastructure

Dark Ice Research is a boutique quant research firm based in Hong Kong, focusing on US and APAC equities. We are hiring a Software Engineer to build and maintain the engineering backbone of the firm — our trading platform and the data infrastructure beneath our research. You will work directly with the founder and senior technical advisors, who set the architecture and review the critical paths; you own the hands-on build.

Trading platform. Maintain a production execution engine on the Interactive Brokers TWS API (ib_insync / ib_async): order lifecycle from submission to fill reconciliation, position tracking, and real-time risk control. Implement pre-trade and real-time risk checks — exposure limits, per-stock position caps, order rate limits, circuit breakers — with a careful approach to error handling, state consistency, and recovery from connectivity failures. You'll be guided on the design of the risk-critical logic and expected to implement it rigorously.

Data infrastructure. Build and maintain the ingestion, storage, and access layer feeding both research and trading: market data and vendor feeds, an in-memory store (Redis) for real-time state and caching, time-series and relational stores, and a REST API / internal service layer exposing point-in-time-correct data to research and trading. Own the reliability, performance, and correctness of this layer.

What we're looking for

• 2-3 years of professional Python engineering, with strong fundamentals in async / event-driven code
• Genuine data-engineering instinct — clean pipelines, sensible schemas, a reflex for data quality
• Fluent, disciplined use of AI coding tools — you use them to move fast and you can tell when the output is wrong
• Exposure to the IB TWS API or a comparable broker API is a strong plus
• Hands-on experience with Redis (or a comparable in-memory store) for caching, state, or pub/sub
• Experience designing and running production REST APIs and backend services on Linux
• Knowledge of US/APAC market structure (tick sizes, board lots, auction periods) is an advantage
• Experience in a quant, prop, or systematic trading environment is welcome but not essential

What you get. Real ownership of systems that go live, close mentorship from senior practitioners, and a path to grow into the platform's technical owner. Compensation is market base plus discretionary annual bonus and long-term incentive.