More jobs:
Test Engineer; SDET
Job in
Chicago, Cook County, Illinois, 60290, USA
Listed on 2026-10-14
Listing for:
LogicGate
Full Time
position Listed on 2026-10-14
Job specializations:
-
Software Development
Software Testing, DevOps, Software Engineer
Job Description & How to Apply Below
Logic Gate is the leading AI GRC platform for the Enterprise, helping governance, risk, and compliance teams limit surprises, strengthen resilience, augment program performance, and confidently quantify impact and business value. Built to provide a centralized view of risk and compliance, with AI intelligence woven into the platform's core, Logic Gate delivers real-time insights and actionable data to help drive current business decisions, with the flexibility to scale alongside evolving business needs.
Recognized as a Leader in the GRC Market, Logic Gate continues to further solidify its position as a best-in-class platform.
Excited about Logic Gate but not familiar with GRC? GRC stands for Governance, Risk, and ComplianceGRC professionals help their companies manage uncertainty, act with integrity, and stay on the right side of the law. The GRC market is rapidly expanding with continuous growth opportunities. The current market size was valued at $50.5 billion in 2024 and is projected to reach $104.5 billion by 2031.Software
Engineer:
Test (SDET)
Location:
Remote or Bellevue, WA (Hybrid), or Chicago, IL (Hybrid)
About the Role As a Software Engineer:
Test at Logic Gate, you will build and scale the automated testing frameworks, pipelines, and tools that guarantee the reliability of the Risk Cloud platform. AI is central to how you work: you are expected to embed AI-driven tooling across test authoring, regression analysis, and coverage expansion to compress delivery timelines and raise the precision of everything you ship. You will design robust automation suites, expand test coverage across the ecosystem, and systematically isolate complex software regressions.
This role is ideal for an engineering-focused QA professional who treats AI as a core part of their craft, takes operational ownership of quality boundaries, and establishes data-driven testing strategies across our platform.
What You’ll DoAutomation Engineering:
Design, build, and maintain scalable automated testing frameworks and end-to-end regression suites using Type Script and Playwright, augmented by AI-driven code generation, to take validation tasks from requirements through continuous deployment.
Testing Pyramid Validation:
Write clean, understandable automation code to validate backend APIs and integration layers, strictly adhering to the testing pyramid to ensure a highly stable and dependable deployment lifecycle.
Swarm Testing & Edge Cases:
Actively contribute to and expand team testing efforts, systematically validating edge cases, error conditions, and happy paths while guiding the broader Engineering Department and QA Analysts on automated testability best practices.
Systematic Debugging:
Independently diagnose and isolate test automation failures and platform defects by reading distributed system logs, analyzing API console data, and utilizing AI-powered Datadog monitoring patterns to accelerate root-cause resolution.
Technical Documentation:
Author clear technical documentation within the codebase and Confluence, including test strategies, automation runbooks, and detailed defect reports to support collective engineering knowledge sharing.
Test Data
Infrastructure: Work operationally with relational databases (PostgreSQL) and advanced platform data stores, utilizing AI tools to query, manage, and optimize automated test data flows.
Agile
Collaboration:
Partner cross-functionally with product managers, feature developers, QA Analysts, and Dev Ops in Agile sprints, accurately estimating validation effort, mapping task prioritization, and raising project dependencies or blockers daily.
Code Reviews & Quality Culture:
Participate actively in regular peer code reviews for both application features and test suites—providing constructive design feedback and ensuring strict compliance with team quality conventions.
Testing Standards & Strategy:
Partner with Engineering Leadership to help define department-wide QA expectations — incorporating AI governance, coverage ownership, automated-vs-manual boundaries, and documentation standards like runbooks — and translate that direction into practices the framework and broader QA function can follow.
QA Analyst Enablement: Partner directly with QA Analysts across squads to build their automation skills; pair on writing tests, review their automation code, and help shift their time from manual regression toward automated coverage.
Testing Standards & Strategy:
Partner with Engineering Leadership to help define…
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