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Kira Learning

AI-driven CS education platform for K-12

QA Automation Lead

Test Automation EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 8 years of experience in quality engineering, test automation, or SDET roles, with experience mentoring or leading engineers.
  • Design and build quality systems rather than only executing tests.
  • A track record of partnering closely with product teams to shape requirements, identify edge cases, and prevent defects early.
  • Experience owning quality for a sophisticated, user-facing web platform.
  • Hands-on experience with performance and load-testing tools such as k6, Artillery, Gatling, JMeter, or Locust, including designing workload models and interpreting latency percentiles, throughput, concurrency, and resource saturation.
  • Strong experience with modern testing frameworks such as Playwright, Cypress, Jest, JUnit, or PyTest, and building automated end-to-end suites in CI/CD.
  • Strong debugging skills across a multi-layer stack, with familiarity testing distributed systems, APIs, and database-backed applications.
  • Experience defining or improving QA processes in a fast-paced startup environment, with practical judgment about when to automate, test manually, and push back.
  • Cloud experience, ideally AWS.
  • Flexibility with work hours and availability outside regular business hours.

Responsibilities

  • Own and evolve quality strategy across frontend, backend, and AI services, including end-to-end test coverage, performance test scaffolding, and load testing.
  • Lead and grow a small QA team by mentoring engineers, setting standards, and managing at least one direct report while remaining hands-on.
  • Partner with product and engineering to define clear acceptance criteria and prevent defects early.
  • Design and implement scalable automated testing across end-to-end, integration, regression, and performance layers.
  • Own performance and load testing for critical workflows, build realistic workload models from production usage, establish baselines and capacity targets, and validate the platform ahead of peak usage.
  • Diagnose performance bottlenecks across test infrastructure, networks, application services, caches, databases, and third-party dependencies, and partner with engineering on remediation.
  • Evaluate and adopt AI-powered tools to accelerate test generation, maintenance, debugging, and coverage.
  • Improve release confidence through stronger CI/CD integration, test observability, and failure diagnostics, and establish quality gates that improve reliability without slowing velocity.
  • Lead post-incident quality improvements, help prevent regressions, and contribute to documentation and runbooks.
  • Perform hands-on manual QA when needed, approximately 10–20% of the time.

Desired Qualifications

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

About the Company

Kira Learning

AI-driven CS education platform for K-12

Kira Learning provides an AI-powered learning platform for K-12 computer science and AI education. It helps educators and students with curriculum templates or from-scratch course creation, video content, custom assessments, and problem-based activities. The platform uses AI to provide personalized feedback and grading, saving teachers time and guiding student learning. It supports classroom, online, or anytime learning, with features like daily practice, streaks, progress sharing, and specific feedback on code to help students fix mistakes. Revenue comes from subscriptions used by schools and individual educators. Compared with others, it focuses specifically on CS/AI education for younger students and uses AI-driven feedback and grading, along with flexible delivery and ready-to-use templates. The goal is to make CS and AI education more effective and scalable by giving teachers tools to personalize instruction and monitor student progress.

Company size
51-200
Company stage
Early VC
Total funding
$22.5M
Headquarters
Palo Alto, CA
Founded
2021

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