SDET, Test Engineering

LogicGate 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, LogicGate 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, LogicGate continues to further solidify its position as a best-in-class platform.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 RoleAs a Software Engineer: Test at LogicGate, 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 TypeScript 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.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.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 DevOps 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 department-wide QA expectations — 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.What You BringRequiredProfessional Experience: 3-5 years of professional experience in software test automation, systems validation, or backend engineering within a high-growth SaaS environment.Core Language Proficiency: Strong programming experience using TypeScript or a comparable scripting language, alongside practical exposure to automated testing frameworks.AI-Augmented Development: Practical experience using AI coding assistants (Cursor, GitHub Copilot, Codex, or Claude Code) as part of a normal workflow—writing effective prompts, building reusable skills or custom instructions, and knowing when to trust, verify, or discard AI-generated output.Testing Strategy Mastery: Deep command of Fowler's Testing Pyramid and the ability to apply it pragmatically - knowing what belongs at the unit, integration, and end-to-end layers and why - complemented by hands-on proficiency writing API tests, functional end-to-end tests, and performance tests to validate quality at every level of the stack.Mentoring and Coaching: Experience coaching or upskilling less-automation-savvy testers or engineers — you multiply impact through others' skills, not just your own code.Autonomous Troubleshooting: Demonstrated ability to independently debug distributed backend microservices by parsing logs and utilizing core enterprise monitoring platforms like Datadog.Nice to HaveAdvanced Data Infrastructure: Familiarity with validating message queues (RabbitMQ), graph databases (Neo4j), or distributed caching layers (Redis) under automated scale conditions.Background validating multi-tenant B2B SaaS applications where strict data isolation, high availability, and security compliance verification tools (like GitLab Ultimate, Sonarqube and Wiz) are paramount.Experience building or maintaining lightweight reporting/dashboards that surface test coverage (automated vs. The anticipated on-target earnings range for the role is $90,000 -118,000 per year + equity + benefits. At LogicGate, our people are the foundation of everything we do. We are committed to delivering an exceptional experience for our employees and our customers by empowering and enabling our people to take ownership, make an impact, and deliver their best work.In addition to offering competitive salary and variable compensation plans, equity options, and flexible health and wellness benefits, we are proud to offer generous PTO, Annual Company Holidays, Health Days, and Summer Fridays.Employees' growth and development are supported throughout their career journey through informal and formal programs and activities, including access to LinkedIn Learning, regular People Leader training, and our internal Mentorship Program. Our CultureAt LogicGate, our culture and employee experience are grounded in our core values of Be as One, Do the Right Thing, Embrace Curiosity, Own It, Empower Customers, and Raise the Bar, which guide how we show up - for each other, our customers, and all we interact with.We encourage everyone to join one of our Employee Resource Groups (AAPI @ LogicGate, Pride at LogicGate, and Women in LogicGate) to participate in and contribute to conversations that foster an inclusive culture.LogicGate also believes strongly in giving back to the communities in which we live and work. Visit our website to learn about our latest recognition.