Ingénieur d’assurance qualité​/Ingénieure d’assurance qualité

Senior AI-First QA Engineer

Location:

Montreal, Hybrid, Full-time.

Our client is a maritime software company building products that help customers make better decisions during live operations. They connect operational, reporting, compliance, optimization, and other business-critical data into one trusted foundation so teams can act while outcomes can still be influenced.

They believe AI is changing product development itself. The best teams will not just use AI occasionally. They will build around it. They will prototype faster, automate more, orchestrate agents, shorten feedback loops, and rethink how products are delivered from idea to release. They are building that kind of team.

Senior AI-First QA Engineer, helping build quality into a new product from the start. This is not a traditional QA role focused on manual testing or maintaining a slow-moving regression suite. We’re looking for a quality engineer who uses AI tools to build coverage fast, evaluates AI-powered features rigorously, and acts as the quality backbone in a rapid-delivery team.

You will work in tight loops with engineers and designers — catching issues early, automating aggressively, and helping the team move faster without compromising on what matters. You should be just as comfortable writing tests yourself as using AI tools to generate and accelerate coverage.

• Design and build automated test suites across backend, frontend, and integration layers.
• Use AI tools to accelerate test generation, coverage analysis, and regression detection.
• Define quality standards for AI-powered features — including agent behavior, LLM outputs, and non-deterministic system responses.
• Integrate quality checks into CI/CD pipelines for fast, automated feedback.
• Work with engineers and designers in tight loops to catch issues before they compound.
• Help define acceptance criteria and edge case coverage alongside the product and engineering team.
• Build and maintain test infrastructure that scales with a fast-moving product.
• Evaluate new AI-assisted testing tools and incorporate the best into the team workflow.
• Contribute to understanding failure modes of AI systems and build tests that surface them.

• Solid experience in QA engineering, test automation, or software quality roles.
• Hands‑on experience building and maintaining automated test suites (unit, integration, end-to-end).
• Experience with Python testing frameworks (pytest and related tooling) and/or JavaScript/Type Script testing (Jest, Playwright, Cypress).
• Understanding of how to test AI-powered features, including evaluation of LLM outputs and agent behavior.
• Comfortable working in fast-delivery environments without heavy documentation overhead.
• Strong debugging skills and ability to reason about complex system behavior.
• Collaborative and direct — comfortable pushing back on quality issues without slowing the team.
• A genuine curiosity about AI — not polite awareness, but active engagement. You have a real point of view on where things are heading, you follow the field, and you are willing to say what you think.
• Self‑awareness about your own strengths and gaps, and a habit of deliberately using AI to cover the latter. We want people who know what they are good at and are honest about what they are not.
• English and French required.

• Experience using AI tools (Claude, Copilot, Cursor, or similar) to write or accelerate test creation.
• Experience testing LLM-based or agent-based systems.
• Experience with CI/CD integration (Git Hub Actions, ArgoCD, or similar).
• Experience with API and contract testing.
• Experience with React component testing and UI automation.
• Familiarity with evaluation frameworks or approaches for AI systems (LLM eval, RAG evaluation, etc.).
• Experience with Python and an interest in the broader stack:
  FastAPI, Lang Chain, and related tooling.

You’ll join a Montreal-based team being built around a new model of product development: senior people, high ownership, fast iteration, and deep use of AI across the full product lifecycle. We think about this with a simple frame: there are farmers and there are plowers. A…