Senior QA Engineer

ClearJet

Austin (TX)

On-site

USD 120,000 - 160,000

Full time

15 hours ago
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Job summary

ClearJet is seeking a Senior QA Engineer to own the health of every release. You own the release gate; if the suite is green, we ship, if red, we fix. This is a high-autonomy, high-consequence role in a distributed, AI-first team.

You'll build AI-driven test generation, API and end-to-end automation (Playwright), and maintain reproducible environments and fixtures. You’ll triage failures and drive reliability across Django/DRF backend and TypeScript frontend.

Responsibilities

  • Own the release gate and define what must be true before code reaches customers.
  • Develop API test automation for Django/DRF surface — contracts, auth and permission boundaries, pagination, error shapes, idempotency.
  • Build end-to-end frontend automation with a modern framework (Playwright) for revenue journeys and support tickets.
  • Create AI-driven test generation and maintenance pipelines that keep suites current as the product evolves.
  • Triage failures with actionable evidence, the failing assertion, and a probable cause, not just a log link.
  • Treat flakes as a defect class with root-cause analysis and bounded remediation.
  • Ensure reproducible environments and seeded, realistic fixtures for reliable failures and passes.
  • Address non-functional coverage where it matters, including performance-related regressions.

Skills

Automation testing
Release ownership
Problem solving

Tools

Playwright
CI/CD
Docker

Job description

About the Role

We're looking for a Senior QA Engineer to own the health of every release.

That sentence is the whole job, and we mean it literally: you own the release gate. If your suite is green, we ship. If it’s red, we don't. Nobody overrides a red gate by asserting that it's probably fine; they either fix the product or fix the test with you.

That authority only works if the gate is trustworthy, which is where the engineering is. A gate that flakes gets ignored within a week. A gate that takes ninety minutes gets bypassed. A gate that passes vacuously - a suite that asserts nothing, a check that skipped, a probe that read an empty response as healthy - is worse than no gate at all, because it looks like coverage. Your real product is a signal the whole company believes without checking.

You will build that signal with AI as your primary lever, not as a garnish. Generating, maintaining, and repairing tests is exactly the kind of work modern models are good at, and a single engineer using them well can hold coverage that used to need a team. We expect you to industrialise that: agents that turn a merged spec into API and end-to-end coverage, that triage a failure to a probable cause before a human opens it, and that keep selectors and fixtures current instead of letting them rot. We're a small, distributed, AI-first team - this is a high-autonomy, high-consequence role, not a ticket queue.

Our surface today: a Python/Django + DRF backend on Postgres and Redis, a TypeScript/Next.js customer-facing app, GitLab CI, Terraform, Docker, and a set of third-party carrier, airline, and tracking integrations that misbehave in ways no unit test will ever predict.

What You'll Own
  • The release gate: One command, one verdict, on every release. You define what must be true before code reaches customers, you make that decision automated and repeatable rather than a judgement call, and you keep the runtime short enough that nobody wants to skip it.
  • API test automation: Broad, fast, deterministic coverage of our Django/DRF surface — contracts, auth and permission boundaries, pagination, error shapes, idempotency, and the integration seams where a carrier or airline API changes its mind without telling us.
  • End-to-end front-end automation: Real browser coverage of the journeys that earn revenue and the ones that generate support tickets, in a modern framework (we'd reach for Playwright), stable enough to run on every merge rather than nightly.
  • AI-driven test generation and maintenance: Build the pipeline that turns a spec into a first-pass suite, keeps suites current as the product moves, and drafts the fix when a selector or fixture goes stale. Maintenance cost is the thing that kills automation programmes; automating maintenance is the point.
  • Failure triage that arrives with an answer: When the gate goes red, the team should get the failing assertion, the diff or deploy most likely responsible, and a first hypothesis — not a link to a log. Increasingly that triage is an agent's first pass and your verification.
  • Flake as a defect class: Track flake rate as a real metric with a real budget. Quarantine, root-cause, and fix — never silence. A test that was muted to unblock a release is a decision that has to expire.
  • Environments and test data: Reproducible environments and seeded, realistic fixtures, so a failure means something and a pass isn't luck.
  • Non-functional coverage where it matters: Performance regressions on the
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