AI-First QA Engineer (Quality & Test Automation) (m/f/d)

EverReal is building the operating system of real estate transactions — our vision is real estate transactions that run themselves. Today we structure and automate transactions. Tomorrow EverReal will run them autonomously, as your digital team member.

Quality is how we earn the trust of 400+ real estate companies who run their business on our platform every day. And we believe the 10x unlock in software isn't AI writing code — it's sharp humans with good judgment directing AI at scale. That belief defines this role. We're not hiring someone to hand-write test scripts all day. We're hiring someone to think, and to operate AI so that quality scales far beyond what one person could test by hand.

Your playing field

You will own quality for the EverReal platform as we scale — and you'll do it as an operator of AI, not a writer of scripts. The model we're building toward: AI implements and runs the tests; you direct it and own the judgment. You won't spend your days reviewing test code line by line — increasingly that's automated, and you look at the results. Your judgment goes where it matters:

• Defining behaviour in clear, correct Gherkin scenarios — the source of truth for what "working" means.
• Reviewing the test cases AI writes (Gherkin and manual) to make sure they're actually right.
• Reading results to decide what's genuinely broken, what's flaky, and what's ready to ship.

AI is the tool; you are the operator. It removes the repetitive mechanics so your judgment scales. This is a deliberately high bar and a real growth path: you start by owning quality hands-on, then progressively push the mechanics onto AI while you keep the standards and the hard calls.

What you'll do

• Own quality and be the last gate. Nothing ships to production without your sign-off. Escalate early when timelines compress.
• Own manual testing & UAT. Exploratory, functional, regression and user-acceptance testing — the human eyes before customers see it.
• Maintain the Gherkin scenarios. The living source of truth for how the product should behave; review the test cases AI generates for correctness.
• Operate the automated testing, don't hand-crank it. Direct AI to implement and run Playwright/E2E and API tests; judge by results and keep the suite trustworthy and green.
• Sign off every release. Run regression, give the go/no-go, post the release notes (AI drafts, you own them).
• Be the first line of defense for production. Validate, reproduce and route customer-reported issues fast, with AI.
• Triage results. Real bug vs. flake, root cause (with AI + Datadog/Sentry), surface only what needs a human call.
• Continuously automate your own work with AI. If you've done it manually twice, make AI do it the third time.
• Prove it with evidence. Clear bug reports with root cause, regression checklists, screenshots, logs and recordings — tests are the documentation.
• Be the product's second brain. Learn the product and users deeply; turn that into the right scenarios and the right questions.

The team you'll join

A small, focused team in agile Scrum: five engineers, QA (you'll work alongside our current QA), and a product manager — all working closely with the CTO, who is still hands-on in engineering. QA is not a downstream function here: you're in refinement from the start, and your sign-off is a hard release gate.

How we work

• AI-native. Claude Code, agents and MCP are first-class infrastructure. Every step goes through AI first, then the person.
• Evidence-driven quality. Every acceptance criterion is proven, not assumed.
• Async-first. Deep-focus mornings are sacred; reviews are batched.
• High psychological safety. Praise in public, feedback in private; we talk about the system, not the person.
• Ownership. Concrete end goals with the context and autonomy to achieve them.

We hire for intelligence, judgment, and curiosity over a tool checklist. Frameworks can be learned in weeks; sharp, structured thinking under ambiguity cannot be taught. Our process includes a short reasoning/aptitude component and a live test-design exercise — how you think matters more than which library you used last. You understand how systems work under the hood (HTTP, APIs, the browser, Docker) well enough to reason about failures and debug when AI gets it wrong — and above all you're a continuous learner.

Must

• Fluent in English (speaking, reading, writing).
• A genuinely sharp problem-solver — structured, analytical, comfortable with ambiguity.
• A continuous learner who adopts new tools without being told.
• Solid grasp of the fundamentals: HTTP, APIs, how the browser works, how Docker works — enough to debug, not just describe.
• 4+ years in QA / software testing, with strong manual, exploratory, regression and UAT experience as well as automation.
• A genuine drive to automate your own repetitive work.
• Strong test-case design and Gherkin / BDD thinking.
• Hands-on E2E and API automation — Playwright (our direction) or strong Cypress with eagerness to switch — and comfort with JavaScript / TypeScript to read, direct and debug.
• Excited to work AI-first and to operate AI — direct it, judge its output, build processes around it.

Nice to have

• Real experience using AI tools (Claude Code, Copilot, agents, MCP) in actual work.
• Experience owning release management / release processes.
• Mobile app automation testing (React Native).
• Basic SQL / PostgreSQL for data-driven testing.
• React.js familiarity.
• Performance/load testing (JMeter, k6).
• ISTQB or similar certification.
• Additional programming languages (Python, etc.).

Our QA stack & process

• Behaviour & test design: Gherkin / BDD scenarios as the source of truth; AI-assisted test-case generation, reviewed by you.
• Test automation: Playwright + TypeScript (migrating off legacy Cypress); Jest for unit; API + UI + mobile emulation — increasingly run via AI.
• AI-native tooling: Claude Code, agent orchestration, Playwright via MCP, plus in-house Sentinel (production analytics MCP) and Autopilot (autonomous coding loop).
• Platform: NX monorepos (pnpm), React 18 + MUI frontend, Node.js/Express + TypeScript backend, Sequelize, PostgreSQL, OpenSearch, AWS.
• CI/CD & ops: GitHub Actions, Datadog + Sentry, environment-based runs (dev / QA / staging).
• Process & tracking: Linear, Slite, Slack, 2-week Scrum sprints, release-readiness sign-off owned by QA.

This is a long-term, open-ended, full-time engagement. It runs on an invoicing setup rather than local payroll — but in every way that matters, you're a full member of the team, not a vendor.

• Goal-driven, not hour-driven. We care about outcomes, not timesheets. You're paid a fixed amount monthly (not hourly).
• 24 vacation days per year, plus the German public holidays (~13 days).
• Yearly team events in Germany — we bring the whole team together in person.
• A company MacBook, if you don't already have one you'd rather use.
• The opportunity to shape how quality works at a scaling, category-defining platform from the ground up.
• Work from anywhere on CET-friendly hours, with a positive, highly motivated international team.
• A learning & wellness budget — we'll actively invest in making you world-class at operating AI for quality.
• A genuinely modern, AI-forward technology stack and a culture that rewards thinking, not box-ticking.

How we hire

We keep the process short, structured, and respectful of your time:

• Screening call — a structured conversation about your experience, how you think, and the way we work.
• A short practical exercise — close to the real work: take a feature, specify its behaviour, and decide what you'd automate versus check by hand. Using AI is encouraged — we care how you direct it and verify its output.
• Final call — meet the team members you'll work with day to day.

We move quickly and give honest, specific feedback at each step. We hire on merit and on how you think — applicants of every background are welcome.