
Key Responsibilities
- Build AI tooling that turns requirements, specs and tickets into test plans and executable test cases
- Use AI agents to write, extend and repair automated tests — and own the judgment call on what they produce: the plausible-but-wrong test, the assertion that can never fail, the coverage that only looks like coverage. This is the core skill of the job.
- Automate execution: suites that run on every change, stay fast, don't flake, and fail in a way someone can diagnose without re-running them locally
- Work with Development and Product Management as their quality partner — help engineers test their own features properly, review test coverage on PRs, stop regressions before production
- Convert manual test cases into automated ones, and keep an honest inventory of what's left and why
- Run the manual testing that still needs a human: exploratory passes on new features, visual and cartographic correctness, complex data flows across data warehouses
- Build the test data the automation depends on — datasets, warehouse connections, maps consuming multiple data sources
- Get deep enough in spatial SQL to validate our analysis output yourself
You offer
- Hands-on use of AI coding assistants (Claude Code, Copilot, Cursor) as a daily working tool, and concrete examples of where they've burned you
- Comfortable writing and debugging TypeScript or JavaScript; you can read the code you're testing
- Playwright, Cypress or a similar modern E2E framework
- API testing experience
- Experience working with SQL — you can query and validate data yourself
- Clear written communication in English; much of this job is explaining risk to developers and PMs
- Experience building AI-driven test tooling — agentic test generation, LLM-based assertions, self-healing selectors, AI-assisted triage
- Nice to have: experience testing GIS or mapping software, CI/CD pipelines (ideally GitHub Actions), BDD/TDD practice or Gherkin, and querying data warehouses like BigQuery, Snowflake, Databricks or Redshift
- +3 years in QA or test automation on a real product
- A track record of automating what used to be manual — the thing we'll dig into most
- The instinct to ask what isn't covered, and to find the edge case the requirements forgot
- Comfort working without a playbook; you'll be proposing the tooling, not waiting for it
- Bachelor's degree in Computer Science, Geography or related fields, or the equivalent learned on the job
- Autonomy, curiosity, real eagerness to learn, and good energy
Benefits
- Competitive, results-based compensation
- Access to our employee stock options plan
- Private medical insurance
- Flexible work hours in a focused but casual environment
- Education Stipend
- Flexible compensation
- English classes
- A big vision: to help the world use location-based data to make better decisions. We believe that openness and sustainability are baked into this vision, and we’re sharing it with the world.
- Contribute to a platform used by top companies around the world. Your work will have a direct impact on our users and clients.
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