Senior QA Lead / QA Manager (GenAI & MLOps Platform)

Experience : 10+ Years

Job Type : Full-time

About Katonic :   We are a young, Aussie Generative AI startup headquartered in Sydney, Australia.

Job Description :

We are seeking a highly experienced Senior QA Lead / QA Manager with 10+ years in quality engineering to own and drive the QA strategy for our enterprise-grade GenAI and MLOps platform. This platform includes LLM-based chatbots, knowledge search and retrieval, web search integration, text and document processing, image processing, connector integrations, persona and brand voice configurations, multi-tenant operations, model fine-tuning, GPU-based LLM deployments, and API-based chatbot interfaces. The ideal candidate will lead QA teams, define scalable test processes, and ensure end-to-end reliability, performance, and security across all AI / ML and platform components.

Key Responsibilities :

Lead and manage the QA team, establishing QA strategy, processes, and governance.

Design comprehensive test plans for GenAI features, including enterprise chatbot, RAG search, Ask-AI modules, guardrails, persona / brand voice workflows, and multimodal pipelines.

Validate ML workflows such as embedding generation, model fine-tuning, LLM deployments on GPU, GPU slicing, resource allocation, and model lifecycle management.

Test platform components : tenancy management, connectors, integrations, microservices, and multi-tenant SaaS modules.

Build and maintain automation for UI, API, backend services, and ML pipelines (functional, regression, integration, and E2E).

Perform performance, scalability, and load testing for chat-based and API-driven systems.

Validate Node.js, Streamlit, Gradio, and Dash applications for stability and compatibility.

Ensure quality coverage for document, text, image, and tabular data processing features.

Collaborate with Engineering, AI / ML, and DevOps teams to ensure high-quality releases.

Drive root-cause analysis, defect management, and continuous improvements across the QA lifecycle.

Required Skills :

10+ years of QA experience with at least 3–5 years in a lead or managerial role.

Strong experience testing GenAI / ML systems, including LLMs, embeddings, RAG pipelines, and multimodal processing.

Hands-on automation expertise using Selenium, Playwright, Cypress, Pytest, Robot Framework, or similar.

Strong API testing experience (Postman, RestAssured, Playwright API, JMeter).

Knowledge of Python, Node.js, or other scripting languages for test automation.

Familiarity with GPU-based model deployment, Docker, Kubernetes, and cloud platforms.

Experience testing multi-tenant SaaS applications, microservices, and real-time chat APIs.

Strong analytical and debugging skills, with an ability to work closely with cross-functional teams.

Preferred Skills :

Experience with MLflow, Kubeflow, or other MLOps tools.

Knowledge of vector databases (FAISS, Pinecone, Chroma, Weaviate).

Experience with guardrails frameworks (NeMo Guardrails, Guardrails AI, etc.).

Exposure to GPU orchestration, vLLM, Triton, or Hugging Face model servers.

What We Offer :

Opportunity to lead QA for a cutting-edge GenAI & MLOps ecosystem.

Work with advanced LLMs, GPUs, embeddings, and multimodal AI technologies.

Collaborative environment with engineering, AI / ML research, DevOps, and product teams.

100% work from home

"Please apply only if you match the criteria.”

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