Job Role: Lead AI Test Automation Architect

Location : Toronto, Canada (Remote)

Experience: 12–14 years

Role Type: Architect / Senior SDET / AI QE Technical Lead

Role Overview The AI QE Architect will lead the design, development, and optimization of next-generation AI-powered quality engineering solutions, including platforms. This role combines deep technical expertise in automation engineering with hands-on experience in LLMs, agentic AI frameworks, and enterprise-grade AI tooling. The architect will define strategy, design scalable frameworks, guide teams, and drive innovation across QE automation, AI agents, RAG pipelines, and MCP-enabled intelligent workflows.

Key Skills & Responsibilities

AI, LLMs & Agentic Systems

- Strong hands-on experience with LLMs, prompt engineering, RAG, vector DBs, and model evaluation.
- Proficiency with LangChain, HuggingFace, Transformers, OpenAI/Ollama APIs.
- Experience to agentic AI frameworks like LangGraph, AutoGen, CrewAI.
- Build and enhance GenAI-powered QE solutions, AI agents, and autonomous workflows.
- Implement MCP-driven, context-aware automation and CI/CD decision intelligence.

Automation Engineering
- Strong coding skills in Python, TypeScript, or Java.
- Architect and maintain automation frameworks for:
- UI: Playwright, Selenium
- API: PyTest,



Requests, RestAssured
- Performance: JMeter, Locust
- Develop prompt-optimized, AI-generated test assets and validation mechanisms.

ML/AI Engineering & Data Pipelines
- Experience with PyTorch, TensorFlow, Scikit-Learn, NLP/CV libraries (NLTK, BART, OpenCV).
- Build data/embedding pipelines and optimize retrieval for RAG.
- Implement CI/CD for ML models, including versioning, evaluation, and retraining workflows.

Cloud, DevOps & Integration
- Robust understanding of AWS/Azure/GCP architectures and AI/ML services.
- Integrate automation pipelines using GitHub Actions, Azure DevOps, Jenkins.
- Ensure scalable, secure, and governed AI/automation environments.

Leadership & Delivery Excellence
- Provide technical leadership and mentor teams on AI adoption and automation best practices.
- Collaborate closely with developers, SMEs, and product teams to align on architecture and roadmap.
- Drive feature prioritization, quality strategy, and solution design.
- Lead defect triage, quality reviews, and compliance with QE/AI governance.
- Work across the full SDLC, contributing to test strategy, design, execution, and analysis.
- Operate effectively in an Agile/Scrum environment.

📌 Lead AI Test Automation Architect (Toronto)
🏢 Apexon
📍 Toronto