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ProjectMark is seeking a QA Engineer to own quality end to end for a multi-tenant CRM and proposal platform used in construction. You’ll perform manual testing and build automated Playwright tests, working within CI to shrink manual effort over time.
You should have 4+ years of web QA experience, strong testing fundamentals, SQL and API testing skills, and comfort with TypeScript/JavaScript; AI-assisted testing experience is a plus and English communication must be excellent.
About ProjectMarkProjectMark is an all-in-one CRM and proposal platform built specifically for the construction industry. We give construction companies the tools they need to manage relationships, streamline their sales process, and win more work. We are a fast-moving team looking for smart, ambitious, accountable people who care deeply about building great software and delivering an exceptional customer experience.
We are looking for a QA Engineer who owns quality end to end: hands‑on manual testing of new features and releases, plus building and maintaining an automated end-to-end test suite in Playwright. Roughly 60% of this job is manual. Reading specs, designing test cases, exploratory testing, running regression passes before release, and writing bug reports an engineer can act on without needing a follow‑up conversation. The other 40% is automation. You take the regression cases you keep running by hand and turn them into Playwright tests that run in CI, so the manual pass gets shorter every quarter instead of longer. ProjectMark is a multi‑tenant B2B platform used by enterprise architecture, engineering, and construction firms. Testing it properly means understanding permissions, tenant isolation, data-heavy workflows, and integrations with Microsoft365, Google Workspace, and construction ERPs. We want someone curious about how the product actually works, not just whether the button responds.We also want someone with disciplined AI-assisted workflows. AI is a core part of how we build and test here, and we expect you to use it well. AI proficiency must complement, not replace, strong testing fundamentals. You must be able to design a test strategy yourself, judge whether AI-generated test code is actually testing anything, and spot the gaps an agent will confidently miss. This role involves some direct contact with our Customer Success team and occasionally with customers, so clear spoken and written English is essential.
We are specifically looking for someone who goes beyond occasionally asking a chatbot for a test case. You should have hands‑on experience with: AI coding agents and editors such as Cursor, Claude Code, Codex, or Windsurf, used to write and maintain real test code. Generating test cases and test data from specifications, then reviewing them critically rather than accepting them. Knowing where AI-generated tests fail: brittle selectors, assertions that can never fail, coverage that looks broad and tests nothing, and false confidence in a green suite. Structured planning, implementation, and verification workflows rather than one-shot prompting. You should be able to clearly explain the process you have developed for testing software with AI, where the agents help, where they mislead you, and how you verify their output.