GenLogs is a transportation-technology company building the next generation of truck intelligence. Through a nationwide network of sensors and proprietary data, we deliver real-time, high-fidelity insights into freight movement for commercial supply-chain customers and public-sector agencies. Our mission is to strengthen America's logistics backbone, combat freight fraud and cargo theft, and provide near-instantaneous visibility into commercial motor vehicle activity across major freight corridors.
ABOUT THE ENGINEERING TEAM
The Engineering team at GenLogs builds and sustains the end-to-end systems that power the country's most advanced commercial-vehicle sensing and intelligence network, from roadside hardware and computer vision pipelines to distributed cloud infrastructure and real-time data services. We own the reliability, accuracy, and security of our sensor network and the data products it fuels. We value technical rigor, speed of execution, and durable infrastructure that delivers mission-critical impact.
ABOUT THE JOBAs a Senior QA Automation Engineer at GenLogs, you bring two things together: the judgment of a senior QA engineer who understands the platform and the business deeply, and the engineering skills to turn that understanding into automated integration and end-to-end test suites. You will use AI tools as a core part of your workflow to design, generate, and maintain tests at a pace manual approaches can't match. Your work directly supports our move toward daily deployments backed by reliable regression gates, where QA owns the release decision.
WHAT YOU’LL DO- Learn the GenLogs platform end to end: our products, data flows, customers, and the freight and transportation domain that drives them.
- Review specs and requirements early, identify gaps and ambiguities, and define clear acceptance criteria before development starts.
- Translate business rules and product specs into clear test strategies, test cases, and acceptance criteria before code is written.
- Design, build, and maintain automated integration and E2E test suites across ReactJS portals and python/NextJS APIs
- Build and evolve a two-tier testing approach: fast mocked suites that run on every pull request, plus scheduled E2E suites against real backends using managed seed data.
- Use AI coding agents and LLM-based tools to generate tests from specs, expand coverage, triage failures, and keep suites healthy as the platform changes.
- Integrate automated suites into CI/CD pipelines as regression gates that protect every release.
- Own the release gate: define quality criteria, report on risk, and make clear go/no-go recommendations.
- Validate data accuracy and integrity using SQL against large-scale datasets.
- Investigate defects and production issues, providing precise reproduction steps and root-cause insight to engineering.
- Partner with product, engineering, and data teams to raise quality standards and make testability part of every design discussion.
- Track quality metrics such as escaped defects, regression trends, and release stability, and turn them into actionable improvements.
- Track and reduce flaky tests, test debt, and gaps in coverage.
- 5+ years of experience in software Quality Assurance, with at least 3 years focused on test automation.
- Strong programming skills in a modern language: Python, Java, Javascript, or Typescript
- Hands-on experience with E2E frameworks such as Playwright or Cypress.
- Solid experience with API and integration testing (pytest, requests, Postman, or similar).
- Proven, practical use of AI tools (Claude Code, Cursor, Copilot, or similar) to write, maintain, and scale automated tests.
- Experience integrating test suites into CI/CD pipelines and working with containerized environments.
- Strong SQL skills for data validation and test data management.
- Experience with test data strategies, including seeding, isolation, and handling non-idempotent operations.
- Exceptional attention to detail and a habit of questioning assumptions in requirements and behavior.
- Excellent written and verbal communication skills, with the ability to explain risk clearly to technical and non-technical audiences.
- High effectiveness working in a remote and distributed team.
- Experience with spec-driven development, where specs drive code, tests, and documentation.
- Experience testing data-heavy or distributed systems, geospatial data, or computer vision outputs.
- Background in logistics, transportation, or supply-chain technology.
- Experience building internal AI-assisted tooling or agent workflows for QA.
- JavaScript/TypeScript experience.
- You learn about the business holistically and you test against how customers actually use the product.
- You catch the edge case others miss and document it so clearly that nobody has to ask twice.
- You treat test code as production code: clean, reviewed, and maintainable.
- You see AI as a force multiplier and you know how to verify its output instead of trusting it blindly.
- You anticipate risk, take initiative, and raise concerns early.
- You value transparency, seek feedback, and build trust across teams.
- You thrive in a remote environment and deliver results with autonomy.
