Role Overview This position is for a Principal Quality Architect who embeds directly with customers as a hands‑on quality partner while also building production features. The role blends test engineering with full‑stack development: you'll help build the systems and the safeguards that prove they work. You'll apply agentic development and AI‑assisted workflows, using behavior‑oriented prompts and specifications to guide AI agents to generate both implementation and verification. A core component of this role involves working directly with customers to modernize their technology estates and raise their quality bar, with the goal of supporting business growth. This is a hands‑on technical role focused on building, verifying, and improving engineering quality. Key Responsibilities Customer Embedding & Delivery: Work directly in customer environments to understand their business, workflows, and technical constraints firsthand. Contribute to the end‑to‑end delivery of solutions from scoping through implementation, verification, and deployment building trust as a reliable partner for both features and quality. Bring clarity to evolving problem spaces. Agentic Quality: Apply an agent‑first methodology using Generative AI. Create structured, behavior‑oriented prompts and specifications that guide AI agents to generate implementation code and the tests that verify it. Confirm that AI‑generated code actually conforms to intent closing the gap between what was asked for and what was built.



Test Strategy & Automation: Design and build test frameworks and automation across the stack; unit, integration, contract, end‑to‑end, performance, and load testing. Help establish quality gates, test orchestration, and coverage standards that scale across polyglot codebases and customer teams. Feature Development: Build production‑grade features alongside your quality work. Contribute to scalable, resilient systems and translate business requirements into technical specifications that AI agents and engineering teams use as the foundation for development. AI‑Assisted Engineering: Integrate AI tools like Claude Code, Kiro and Cursor into development and testing workflows. Evolve your engineering practice from manual coding and test‑writing to auditing, validating, and refining AI‑generated solutions. Apply the judgment to catch coverage theatre, AI‑generated tests that pass but prove nothing. Follow repeatable AI‑driven development patterns. Design for Quality: Build with testability, resilience, and observability in mind from the outset. Participate in implementation reviews to ensure alignment with patterns, performance, and security expectations. Polyglot Development: Write and test production‑grade code across multiple languages and paradigms (e.G., TypeScript, Python, Go, .NET, Java) based on specific problem domains. Ramp into unfamiliar stacks or codebases. Enablement & Knowledge

📌 Principal Quality Architect (Toronto)
🏢 Carbon60
📍 Toronto