Quality Assurance Engineer

Role Overview

Join h2o.ai as a Quality Assurance Engineer to ensure the quality and reliability of the product portfolio. You will build automation frameworks, conduct exploratory/manual testing, and work closely with feature teams in an Agile environment.

Key Missions

• Design, build, and maintain Python-first automation frameworks for:
  • UI testing
  • API testing
  • end-to-end workflows
• Perform deep exploratory and manual testing of the product portfolio web UI, including creative use of generative AI tools for testing support.
• Collaborate with feature teams in Agile, influencing testability from the design phase.

Profile / Requirements

• Python skills; experience creating maintainable test frameworks from scratch
• Ability to use generative AI tools daily to accelerate:
  • debugging
  • test-data creation
  • log analysis
• Strong understanding of CI/CD, with GitHub Actions preferred
• Familiarity with infrastructure-as-code concepts
• Ability to read and triage complex logs from:
  • LLM frameworks
  • vector databases
  • tracing systems
• Hands-on Kubernetes experience in a testing/test-environment context (e.g., kubectl, Helm, manifests, debugging pods)
• Experience testing React/TypeScript web applications and writing reliable tests using Playwright or Selenium
• 2–4 years of QA experience with a strong mix of automation and exploratory/manual testing

Nice-to-Haves

• Experience testing RAG systems, agentic workflows, or enterprise chat/assistant platforms
• Experience with visual diffing of generated outputs (documents/charts/markdown)
• Chaos engineering on Kubernetes (e.g., Chaos Mesh, Litmus) or GPU workloads
• Basic containerization knowledge (Docker/Kubernetes concepts like pods and kubectl)
• Familiarity with Chaos engineering principles