Trading Systems SDET: AI/ML QA & Low-Latency Test Engineer

SpiderRock; Chicago (IL); On-site; USD 110,000 - 180,000; Full time

Benefits offered by this job

401K plan and matching

Employee assistance program

Gym membership

Unlimited snacks

Job summary

SpiderRock is seeking a sharp, technically deep SDET to own quality across trading systems, from order execution engines to real-time risk analytics. You will work with quants, traders, and engineers to ensure the platform behaves correctly under normal and edge-case market conditions.

Your role includes testing AI/ML models and LLM tools used internally and building robust CI/CD gates. Requirements include 4+ years in SDET/QA in financial services, proficiency in Python and/or Java/C++, and

Qualifications

• 4+ years of SDET or QA Engineering experience, with at least 2 years in financial services or trading systems.
• Proficiency in Python and/or Java/C++ for test automation.
• Strong understanding of options trading concepts — calls/puts, expiry, strike, Greeks, volatility surfaces.
• Hands-on with test frameworks: pytest, JUnit, TestNG, or equivalent.
• Familiarity with ML concepts — model training, inference, overfitting, feature importance, and evaluation metrics (precision, recall, AUC).
• Solid fundamentals in data structures, algorithms, and distributed systems.
• Familiarity with SQL and time-series databases (kdb+, InfluxDB, TimescaleDB).
• Experience with CI/CD tools (Jenkins, GitLab CI, GitHub Actions).
• Ability to read and reason about quantitative models and pricing logic.
• Experience writing LLM evaluation frameworks — prompt regression testing, output scoring, and consistency checks across model versions.
• Familiarity with MLflow, Weights & Biases, or SageMaker for model lifecycle tracking and test integration.
• Knowledge of AI governance and model risk management frameworks (SR 11-7 or equivalent) relevant to financial institutions.
• Experience with market simulators or exchange emulators.
• Knowledge of regulatory requirements (FINRA, SEC, CFTC) and audit trail testing including AI-assisted decision logging.
• Exposure to co-location or FPGA-based trading infrastructure.
• Familiarity with chaos engineering and fault injection testing.
• Prior experience with kdb+/q for tick data validation.
• Contributions to open-source testing or ML evaluation tools.

Responsibilities

• 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.

Skills

Python

Java/C++

Test frameworks

ML concepts

Data structures

SQL

Time-series DBs

LLM evaluation

Model governance

Market simulators

Chaos testing

Open-source tests

FPGA exposure

Tools

Jenkins

GitHub Actions

GitLab CI

Job description

SpiderRock is seeking a sharp, technically deep SDET to own quality across trading systems, from order execution engines to real-time risk analytics. You will work with quants, traders, and engineers to ensure the platform behaves correctly under normal and edge-case market conditions.

Your role includes testing AI/ML models and LLM tools used internally and building robust CI/CD gates. Requirements include 4+ years in SDET/QA in financial services, proficiency in Python and/or Java/C++, and