QA Engineer — AI-Powered Test Automation

Hybrid
Praha
Full-time

About SingleCase

SingleCase is an AI-native legal practice management platform serving law firms across Europe. We build software that helps lawyers manage cases, clients, time, billing, and documents — all in one place. We are a small, high-ownership team building a serious product for a demanding industry. Quality is foundational to what we do, and we believe AI is fundamentally changing how quality is achieved.

The role

We are looking for a QA engineer who thinks of themselves primarily as an AI workflow builder and testing architect — someone who uses AI to multiply testing capacity, not just as a convenience tool.

This is not a role for someone who wants to manually execute test cases. We have a fast-moving roadmap, a lean team, and high standards. The person in this role will design and orchestrate automated testing systems — using AI agents, LLM-assisted test generation, and smart automation — so that our QA coverage scales independently of headcount.

You will own the testing strategy end-to-end: what gets automated, how AI is used to generate and maintain tests, and how quality gates are enforced throughout the development lifecycle.

What you will do

Design and operate AI-assisted testing workflows — using LLMs to generate test cases from specs and acceptance criteria, reducing the time from requirement to test coverage to near zero
Build and maintain end-to-end automated test suites using Playwright (or equivalent), with AI actively generating, reviewing, and maintaining test scripts
Act as testing orchestrator: define what AI handles autonomously, what requires human judgment, and architect the system accordingly
Integrate AI-powered test generation into our CI/CD pipeline so that new features arrive with tests, not after them
Use AI agents for exploratory testing — running autonomous sessions that surface edge cases human testers would miss
Own regression testing strategy: continuously evaluate which tests to automate, retire, or hand to AI maintenance
Work with product and developers at the spec stage — shaping features for testability before a line of code is written
Monitor, triage, and communicate quality signals clearly — not just filing bugs but giving the team a live view of product health
Research and evaluate new AI testing tools as the space evolves rapidly — we expect this role to stay ahead of the curve

What we are looking for

Genuine enthusiasm for AI-assisted and AI-driven testing — this is the core of the role, not an add-on
Hands-on experience building automated test suites (Playwright, Cypress, Selenium, or similar) — you write the code, not just configure the tool
Experience using LLMs or AI coding tools in a testing or QA context — prompt engineering for test generation, AI-assisted debugging, or autonomous test agents
Comfortable with TypeScript or JavaScript; Python is a bonus
Experience with API testing (REST/GraphQL) and CI/CD integration (GitHub Actions or similar)
Systems thinker: you design processes and tooling, not just individual tests
Strong communicator — quality signals are only useful if the team understands them

Nice to have

Experience with AI testing frameworks or agents (e.g. Autify, Reflect, Momentic, or custom LLM-driven test runners)
Background in SaaS B2B products, legal tech, or other compliance-sensitive domains
Exposure to performance or load testing (k6, Locust)
Familiarity with accessibility testing
A feel for UX and product design — the ability to spot when something works technically but feels wrong to a user, and to communicate that clearly to the product team

What we offer

Full ownership of the testing strategy and AI tooling stack — you define how quality works here
A team that takes AI seriously: budget, time, and genuine support to build AI-first workflows
Direct influence on product decisions — QA is involved from the start, not bolted on at the end
Small team, high visibility — your work shapes the product, not just verifies it
Hybrid work from Prague with flexible hours
Competitive salary benchmarked against the Czech tech market

Hiring process

1. Intro call (30 min) — we want to hear how you think about AI in testing and what workflows you have built or would build.

2. Technical task — a realistic, time-boxed exercise centred on AI-assisted test design. We keep it under 2 hours and respect your time.

3. Technical interview (60 min) — walk us through your approach, your tool choices, and how you would architect our test automation.

4. Final conversation with CTO and product lead.