Senior Quality & Automation Engineer

What You’ll Do

• Ensure a high-quality, reliable experience for teachers and students across web, API, and AI-driven workflows
• Define and evolve our quality strategy across frontend, backend, and AI services
• Design and implement scalable automated testing across end-to-end, integration, regression, and performance layers
• Own performance and load testing for critical workflows, including login surges, classroom activity, assignment submissions, real-time features, and AI services
• Build realistic workload models from production usage patterns, establish performance baselines and capacity targets, and validate that the platform can handle expected traffic before critical launches and peak usage periods
• Diagnose performance bottlenecks across test infrastructure, networks, application services, caches, databases, and third-party dependencies, then partner with engineering teams on remediation
• Evaluate and adopt modern AI-powered tools to accelerate test generation, maintenance, debugging, and coverage
• Partner closely with product and engineering to define clear acceptance criteria and prevent defects early in the development process
• Improve release confidence through stronger CI/CD integration, test observability, and failure diagnostics
• Establish pragmatic quality gates that improve reliability without unnecessarily slowing product velocity
• Lead post-incident quality improvements and help prevent regressions
• Mentor engineers on writing effective, maintainable tests and building testable systems

What We’re Looking For

• 6+ years of experience in quality engineering, test automation, or SDET roles
• Strong experience with modern testing frameworks such as Playwright, Cypress, Jest, JUnit, or PyTest
• Hands-on experience with performance and load testing tools such as k6, Artillery, Gatling, JMeter, or Locust
• Experience designing representative workload models and interpreting latency percentiles, throughput, concurrency, error rates, and resource saturation
• Ability to distinguish genuine application bottlenecks from limitations or unrealistic behavior in the test harness, test data, or load-generation infrastructure
• Familiarity with testing distributed systems, APIs, and database-backed applications
• Experience working in cloud environments, ideally AWS
• Strong debugging skills and the ability to trace issues across multiple layers of a system
• Experience with our stack including Next.js and React frontends, Kotlin and Java Spring Boot backends, Python FastAPI AI services, and LangSmith agent workflows
• Experience defining or improving QA processes in a fast-paced startup environment
• Practical judgment about when to automate, when to test manually, and when to push back
• Clear communication skills across technical and non-technical audiences
• Comfort operating in a fast-moving, high-ownership environment with changing priorities
• High attention to detail and strong product intuition

Nice to Have

• Experience testing AI- or LLM-backed features, including evaluating nondeterministic outputs, prompt regression testing, latency budgets, and graceful degradation when model providers experience issues
• Experience using application performance monitoring, distributed tracing, logs, and cloud infrastructure metrics to identify system bottlenecks
• Experience building internal tooling that improves developer velocity

What Success Looks Like

• Fewer high-severity bugs reaching production
• Greater automated coverage of critical product workflows
• Repeatable performance tests that identify scaling risks before they affect teachers and students
• Clear performance baselines and capacity expectations for peak usage periods
• Faster, more confident releases
• Quality standards that engineers respect rather than bypass
• AI-assisted QA processes that meaningfully reduce manual effort