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QA Automation Tech Lead

Canopy, South Jordan, UT

About Us

Canopy is a fast-growing SaaS company in South Jordan, Utah building simple, powerful software for accounting firms. We're on a mission to help accountants build an autonomous firm — giving them back the time and tools they need to focus on what matters most: their clients.

We believe the accounting industry deserves world-class software, and we're building exactly that. Our Practice Management Suite is purpose-built for firms that want to work smarter, grow faster, and deliver more value to the people they serve. We place a strong emphasis on delighting our customers, spotting and solving problems, and being good people along the way.

Click here to see why our clients (and investors) love Canopy.

Interested in learning more about Canopy & the industry? Check out our blog here where you can find great information on our product features, industry news, practice management, and more!

We are seeking a QA Automation Tech Lead with a high-level engineering pedigree to spearhead the evolution of our quality infrastructure. In this pivotal role, you will serve as the technical authority for automation across the organization while acting as the QA Automation Engineer on our Platform Squad.

Your mission is two-fold: building the foundational infrastructure that enables other squads to scale, and pioneering AI-driven tooling that empowers our manual QA engineers to transition into automation seamlessly. You won't just be maintaining a framework; you will be architecting a self-service quality ecosystem.

This position is remote eligible for candidates who currently reside in Utah.

• Architect & Innovate: Serve as the Lead IC for the Platform Squad, designing and scaling global automation infrastructure that other product squads consume.
• AI Tooling Development: Build and deploy internal agentic AI tools and wrappers designed to lower the barrier to entry for manual QA engineers, enabling them to generate and maintain automated tests autonomously.
• Technical Mentorship: Provide high-level guidance and code reviews for QA engineers across the company, establishing "Golden Paths" for automation excellence.

• Next-Gen Frameworks: Overhaul and scale our Python/Pytest frameworks to support high-concurrency, multi-tenant environments and complex CI/CD integrations.
• Infrastructure as Code: Work closely with DevOps to ensure testing environments are ephemeral, scalable, and integrated into the deployment pipeline via GitHub Actions.
• Advanced API Validation: Move beyond standard assertions to build deep-level API validation suites and maintain centralized Postman collections for cross-team use.

• Data Engineering for QA: Craft complex SQL scripts and data generation utilities to simulate production-grade data across our testing environments.
• Observability: Leverage Datadog and other monitoring tools to implement "Shift-Right" testing strategies, using production telemetry to inform automation priorities.

• Leadership Experience: 6+ years in QA Automation with at least 1-2 years in a Lead or Staff capacity, specifically influencing technical direction or managing large-scale projects.
• Technical Mastery: Expert-level proficiency in Python. You should be comfortable building custom libraries, wrappers, and CLI tools from scratch.
• UI Automation Craftsmanship: Hands-on experience with modern UI testing frameworks (e.g., Playwright, Cypress, or Selenium). You write stable, deterministic tests and treat maintainability and low flakiness as first-class engineering concerns.
• AI/ML Enthusiast: Hands-on experience (or deep technical projects) involving LLM integration or agentic AI to solve engineering bottlenecks.
• Database Depth: Strong ability to write complex SQL queries and understand relational database architecture.
• Platform Mindset: Experience building infrastructure for other engineers. You understand that your "customers" are often the developers and QA peers in other squads.
• Communication: The ability to translate complex technical requirements into actionable roadmaps for both technical and non-technical stakeholders.

• Cloud Native: Deep experience with AWS (Lambda, RDS, S3) and containerization (Docker/Kubernetes).
• DevOps Savvy: Experience building custom GitHub Actions or complex CI/CD workflows.
• Data Pipelines: Familiarity with validating data warehouses (Snowflake/BigQuery) or ETL pipelines.
• Open Source: Contributions to testing frameworks or AI-related open-source projects.

Note to Candidates: This is a high-impact role for an engineer who loves to code but wants the responsibility of shaping the future of quality at a platform level. If you prefer building tools over just writing test scripts, we want to talk to you.

We know many women do not apply for a job if they don't perfectly fit the description. We want you to apply anyway.

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