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Founded in 2012, H2O.ai is on a mission to democratize AI. As the worldwide leading agentic AI company, H2O.ai converges Generative and Predictive AI to help enterprises and public sector agencies develop purposebuilt GenAI applications on their private data. With a focus on Sovereign AIsecure, compliant, and infrastructureflexible deploymentsH2O.ai delivers solutions that align with the highest standards of data privacy and control.Our opensource technology is trusted by over 20,000 organizations worldwide, including more than half of the Fortune500. H2O.ai powers AI transformation for companies like AT&T, Commonwealth Bank of Australia, Chipotle, Workday, Progressive Insurance, and NIH.H2O.ai partners include NVIDIA, Dell Technologies, Deloitte, Ernst & Young (EY), Snowflake, AWS, Google Cloud Platform (GCP), VAST Data and MinIO. H2O.ais AI for Good program supports nonprofit groups, foundations, and communities in advancing education, healthcare, and environmental conservation. With a vibrant community of 2 million data scientists worldwide, H2O.ai aims to cocreate valuable AI applications for all users.H2O.ai has raised $256 million from investors, including Commonwealth Bank, NVIDIA, GoldmanSachs, WellsFargo, CapitalOne, NexusVentures and NewYorkLife.About This OpportunityYou will be a core QA engineer responsible for the endtoend quality and reliability of h2o.ais product portfolio.This is a remote position, with a preference for candidates based in Canada within the PST timezone.What You Will DoDesign, build, and maintain Pythonfirst automation frameworks (pytest + Playwright + async) for UI, API, and endtoend workflows of h2o.ais product portfolio.Perform deep exploratory and manual testing of the h2o.ais product portfolio web UI (chat interfaces, document upload/processing, agent builder, maker suite, evaluation hub, enterprise admin console).Use h2o.ais product portfolio itself (and other GenAI tools) in creative ways to:Generate realistic test documents, datasets, and edgecase prompts.Autogenerate or refine test cases via prompt engineering.Rapidly summarize and debug massive, complex log files (e.g., Kubernetes pods, etc.).Explain cryptic LLM traceback chains or hallucination root causes in seconds instead of hours.Rootcause of difficult, intermittent failures in distributed RAG/LLM systems by combining traditional log analysis with GenAIassisted debugging.Create and execute chaos experiments targeting LLM routing, vector database latency, GPU OOM, retrieval failures, and tokenlimit edge cases.Build and manage ephemerally h2o.ais product portfolio clusters on Kubernetes for testing (Helm, custom operators).Own UI regression suites (Playwright) and accessibility testing.Write reproducible, highquality bug reports that developers love and regularly verify fixes across the full stack.Collaborate closely with the h2o.ais product portfolio feature teams in an Agile environment and influence testability from the design phase.What We Are Looking For24 years of QA experience with a strong mix of automation and handson manual/exploratory testing.Decent Python skills and experience building maintainable test frameworks from scratch.Realworld experience testing modern React/TypeScript web applications and writing bulletproof Playwright or Selenium tests.Handson Kubernetes experience in a testing or testenvironment context (kubectl, Helm, writing manifests, debugging pods).Proven ability to use generative AI tools daily to accelerate debugging, testdata creation, and log analysis (youve already used h2o.ais product portfolio, ChatGPT, Claude, or similar in your current QA workflow).Comfort reading and triaging complex logs from LLM frameworks, vector DBs, and tracing systems.Solid grasp of CI/CD (GitHub Actions preferred) and infrastructureascode concepts.How to Stand Out From the CrowdPrior 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 (Chaos Mesh, Litmus) or GPU workloads.Familiarity with Chaos engineering principles.Basic understanding of containerization (Docker/Kubernetes concepts like pods and kubectl) in a testing context.Why H2O.ai?Market leader in total rewards.Remotefriendly culture.Flexible working environment.Be part of a worldclass team.Career growth.Base salary range: $80,000 - $95,000 CAD.H2O.ai is committed to creating a diverse and inclusive culture. All qualified applicants will receive consideration for employment without regard to their race, ethnicity, religion, gender, sexual orientation, age, disability status or any other legally protected basis.Please visit to learn more. #J-18808-Ljbffr