Unboxed Training & Technology

QA Engineer

• Own and execute the end-to-end test strategy across the platform, including exploratory testing, regression coverage, and release verification.
• Maintain critical-path coverage for the workflows with the highest client impact and SLA exposure and extend automated testing where it produces durable value.
• Serve as the final quality gate before release, owning go/no-go recommendations and flagging risk to Product and Engineering rather than making ship decisions unilaterally.
• Define how quality is measured for AI-generated scoring, feedback, and roleplay, using evaluation approaches that account for output variability rather than exact-match expectations.
• Build test sets, rubrics, and monitoring that surface regressions in AI quality, and partner with AI Engineering to validate changes to models, prompts, and scoring logic.
• Translate client trust concerns into concrete, testable acceptance criteria the team can verify before and after release.
• Own the QA metrics that measure quality health, including Defect Escape Rate, Critical Path Coverage, and MTTD/MTTR, and report on them on a regular cadence.
• Maintain and apply a defect severity rubric that produces consistent triage across products.
• Provide quality reporting to leadership, including trends, risk areas, and consciously accepted coverage gaps.
• Partner with contract engineering and QA teams, establishing and maintaining the process, test conventions, and ways of working they operate within, and keeping those standards current as the platform evolves.
• Set clear acceptance criteria and definitions of done, and review output so it meets the same bar as in-house work.
• Serve as the quality point of accountability across in-house and contract contributions, so external capacity does not dilute the quality signal.
• Directly manage two QA Engineers with a coaching-first approach, owning their prioritization, technical growth, and performance.
• Set and enforce standards for how tests are written, defects are documented, and coverage decisions are made, and grow each engineer's ability to reason about quality independently, so the team's judgment scales without requiring the Lead in every decision.
• Partner with Engineering to shift quality earlier, embedding testability and clear acceptance criteria into development rather than inspecting quality in at the end.
• Work with Support and Implementation to close the loop on client-reported defects, using field escalations from strategic accounts to sharpen coverage.

QA Engineering Lead