Hiring an algorithmic trading developer is different from hiring a general software engineer. The role connects software design with market data, broker APIs, execution behavior, risk controls, and capital exposure.
Test for production judgment
A strong candidate should think about logging, retries, idempotency, rate limits, reconciliation, secrets, monitoring, and failure modes. Trading systems fail in ways that general CRUD applications often do not.
Evaluate data and backtesting skill
The developer should understand timestamp alignment, lookahead bias, corporate actions, missing data, slippage, and realistic simulation. Backtesting mistakes can create false confidence before deployment.
Look for communication around risk
Trading developers should be comfortable asking about max loss, exposure limits, order constraints, and operational procedures. A developer who only asks about features may miss the real risk surface.
Strategic takeaway
The best algorithmic trading developers combine engineering discipline with market-aware skepticism. They build systems that are useful and hard to misuse.
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