QA tester

Junior QA Engineer (Part-Time, Remote)

We're hiring a Junior QA Engineer to help safeguard the quality of our software releases and the data that flows into our machine learning pipelines. You'll sit at the seam between traditional application testing and data validation — making sure new AI features ship without breaking existing systems, and that the data feeding our models is clean before it gets there.

Why this role exists

We're scaling our AI features fast, and every new model deployment is a chance to introduce a regression into the core app or to train on data that quietly drifted out of shape. We need a careful, curious tester who treats every release as a set of specific risks to check — not a checkbox to tick — so finance-critical flows and ML pipelines stay reliable as the product grows.

What you'll do

Release regression testing. Own the manual regression checklist for each core software release. Walk the money paths, the boundary inputs, and the error paths — not just the happy demo — and flag anything that behaves differently from the last stable build.

Data validation for ML pipelines. Run structured validation checks on the data flowing into our machine learning pipelines: schema shape, null rates, value ranges, and the boundary cases (empty batches, malformed rows, unexpected encodings) that quietly poison model training if nobody looks.

Bug reporting that gets fixed on the first pass. Document defects with a minimal reproduction, clear expected-vs-actual behavior, and a severity call with rationale — so engineers can act without a follow-up conversation.

Verification and collaboration. Partner with the engineering team to verify bug fixes actually close the underlying defect (not just the reported symptom) and to sanity-check new feature deployments before they reach users.

What we're looking for

Solid manual testing instincts — you read a feature and can list what could go wrong beyond the happy path.

Clear, structured bug reporting: minimal repro steps, expected vs actual, severity with reasoning.

Comfort writing test cases that target boundaries and failure paths, not just the demo scenario.

Basic familiarity with software development lifecycles and how releases move from dev to production.

Curiosity about data — you're eager to learn how to validate the shape and quality of data feeding ML pipelines.

Strong written English for tickets, checklists, and async collaboration with a remote team.

Nice to have

API testing with Postman (or similar) — sending requests, inspecting responses, checking status codes and payload shapes.

Basic SQL for spot-checking data in a warehouse or database.

Exposure to any ticketing / bug-tracking system (Jira, Linear, GitHub Issues).

Curiosity about test automation frameworks — you'd like to learn Playwright or Selenium down the road.

What success looks like

Within your first 60 days, you'll have established a structured manual regression checklist for our core software releases, so new AI feature deployments stop introducing regressions into existing systems. Ongoing, success looks like a low rate of post-release bugs reaching production and consistent data validation checks running before every major model deployment.

Logistics

Part-time, fully remote from Egypt. Compensation is EGP 20,000-30,000 per month. Reports to a Senior SDE and works closely with a small engineering team (2-5 people). Application deadline: 31 July 2026.

Benefits

Fully remote, part-time schedule — good fit alongside study or another commitment

Direct mentorship from a Senior SDE and a clear path into automation and ML QA

Annual learning budget for QA and testing certifications