Develop end-to-end, integration, and unit test suites covering options pricing models (Black-Scholes, binomial trees), order lifecycle, and P&L calculations

Test and validate AI/ML models used in signal generation, volatility forecasting, and trade execution — including drift detection, model regression, and output boundary testing

Build evaluation harnesses for LLM-powered tools used internally (e.g., trade summarization, risk Q&A, alert triage) to assess accuracy, hallucination rates, and latency

Simulate realistic market scenarios including high-volatility events, expiry dates, and corporate actions to stress-test system behavior

Validate FIX protocol messaging, OMS/EMS integrations, and exchange connectivity (CBOE, ISE, etc.)

Collaborate with quants to write test cases that verify Greeks (delta, gamma, vega, theta) and pricing accuracy under various market conditions

Build performance and load testing harnesses to validate sub-millisecond latency requirements

Design data quality pipelines to validate training data, feature stores, and model inputs for correctness and consistency

Participate in code reviews and advocate for testability in system design

Own CI/CD pipeline quality gates, including ML model promotion gates (shadow mode, A/B, champion/challenger)

Investigate production incidents and translate findings into regression tests