Planned hiring
Software Engineer, Quality Assurance
Lucy is a proactive AI coach from Lucy Labs that lives on your desktop as a cloud-backed app.
Planned hiring. This description explains the work we are preparing to hire for; it is not a confirmed start date or offer.
Make release decisions about Lucy's integrated desktop and cloud experience rest on reproducible evidence. You will test whether the whole product behaves as intended for workers and administrators, especially where permissions, data movement, AI outputs and service failures meet. Your work helps the team find consequential problems early and explain remaining risk honestly.
Your mission
Make release decisions about Lucy's integrated desktop and cloud experience rest on reproducible evidence. You will test whether the whole product behaves as intended for workers and administrators, especially where permissions, data movement, AI outputs and service failures meet. Your work helps the team find consequential problems early and explain remaining risk honestly.
What you will build
- Create a risk-based release matrix for the supported Windows and macOS devices and agreed product journeys, spanning permissioned observation, coaching delivery, correction, user settings and organization administration.
- Build maintainable integration and end-to-end automation, with focused exploratory testing for behavior that scripted checks miss. Use representative, permissioned or synthetic fixtures with controlled tenant boundaries and reproducible setup.
- Exercise immediate pause, lost permissions, offline recovery, retry duplication, incompatible schemas and partial service failure. Verify that local and cloud state agree and that private material does not appear in diagnostics or unauthorized views.
- Test accessibility, responsiveness and resource behavior alongside functional correctness. Explain which users or workflows a failure affects and provide evidence that developers can use to reproduce it.
- Verify retention and deletion journeys with Data Engineering and Product Security, including derived stores and replay behavior. Test configured team-size visibility and allowed individual-statistics opt-in without exposing prompts or Content to managers.
- Combine software verification with independent AI evaluation results in a versioned release record. Make failed checks, untested areas and accepted limitations explicit, then confirm fixes through meaningful regression coverage.
Your partners and boundaries
Every engineer owns component tests and defects in their work. You own integrated verification and the evidence linking a release candidate to user-facing acceptance. Evaluation owns inference-quality methods and datasets; Product Security owns technical security requirements and specialized control assessment. Product defines intended outcomes and participates in risk decisions. Platform/SRE provide deployment and recovery environments. QA does not become a substitute for these responsibilities or the sole person expected to keep all services running.
What you bring
You have written test automation for software that crosses client and service boundaries and can investigate a failure beyond the visible symptom. You understand API contracts, state transitions, asynchronous processing and useful fixture design. You can balance exploratory testing with automation and recognize tests that pass without proving the intended behavior. Experience with native desktop software, accessibility and performance testing is valuable. Clear defect reports and evidence-led release judgment matter more than a particular testing framework.
Your first 90 days
Agree the pilot workflow and device coverage with the implementation owners. Build a small dependable regression suite around the highest-risk journeys and document its gaps. Reproduce one failure across system boundaries and verify its repair. Produce a release evidence record that combines product, privacy and AI-quality checks, with named owners for unresolved items and a repeatable path for the next candidate.
Next step
Express your interest
Email people@lucylabs.ai with the role title, a short introduction and relevant CV or portfolio. This is planned hiring; we will confirm current availability and the individual working arrangement.
Lucy Labs confirms the working arrangement, employer, location, eligibility, compensation and terms for each role. Our mailing address does not determine the job location or guarantee remote employment, worldwide eligibility or visa sponsorship.
Do not send passwords, government identifiers or bank details. Read the application privacy notice.
Frequently asked questions
Is this role open at Lucy Labs?
Lucy Labs lists this role as planned hiring. Availability depends on the need, team readiness and individual arrangement; it does not promise an immediate vacancy or start date.
Where does this work take place at Lucy Labs?
Lucy Labs confirms the working arrangement, employer, location, eligibility, compensation and terms for each role. Our mailing address does not determine the job location or guarantee remote employment, worldwide eligibility or visa sponsorship.
What does this role own at Lucy Labs?
Lucy Labs: Make release decisions about Lucy's integrated desktop and cloud experience rest on reproducible evidence. You will test whether the whole product behaves as intended for workers and administrators, especially where permissions, data movement, AI outputs and service failures meet. Your work helps the team find consequential problems early and explain remaining risk honestly.
How do I express interest in Lucy Labs?
Email people@lucylabs.ai with the role title, a short introduction and relevant CV or portfolio. Lucy Labs uses the application to assess and respond to it; retention for future opportunities is a separate explained purpose and choice.
