SDET/QA Engineer

Overview: SDET/QA Engineer Downtown Chicago - Onsite About The Role: Seeking a technically strong SDET to ensure quality across trading systems, order execution, real-time risk analytics, and AI-driven models. What You'll Do: Develop end-to-end, integration, and unit tests for options pricing, order lifecycle, and P&L. Validate AI/ML models, including signal generation, forecasting, regression, and drift detection. Test LLM-powered tools for accuracy, latency, and hallucination detection. Simulate volatile market events, expirations, and corporate actions for system validation. Verify FIX protocol messaging, OMS/EMS integrations, and exchange connectivity. Partner with quants to validate Greeks and pricing model accuracy. Build performance/load tests to meet sub-millisecond latency requirements. Ensure data quality across training data, feature stores, and model inputs. Support code reviews and improve testability across applications. Manage CI/CD quality gates, including AI/ML model deployment validation. Investigate production issues and create regression tests to prevent recurrence. What We're Looking For: 4+ years of SDET/QA experience, including 2+ years in financial services or trading systems. Proficient in Python and/or Java/C++ test automation. Strong knowledge of options trading, Greeks, and pricing models. Experience testing real-time, event-driven systems (Kafka, FIX, WebSockets). Hands-on with pytest, JUnit, TestNG, or similar frameworks. Understanding of AI/ML concepts, model validation, and evaluation metrics. Experience testing end-to-end ML pipelines and data workflows. Strong SQL, algorithms, data structures, and distributed systems knowledge. Familiarity with time-series databases (kdb+, InfluxDB, TimescaleDB). Experience with CI/CD tools (Jenkins, GitLab CI, GitHub Actions). Ability to validate quantitative models and pricing logic. Experience evaluating LLMs and AI model performance. Familiarity with ML lifecycle tools (MLflow, SageMaker, Weights & Biases). Knowledge of AI governance, model risk, and financial regulations (FINRA, SEC, CFTC). Experience with market simulators, exchange emulators, or low-latency trading environments. Exposure to FPGA/co-location infrastructure, chaos testing, or kdb+/q is a plus. Open-source testing or ML evaluation contributions preferred.

OOJ-1483G