QA Engineering Lead

Unboxed Training & Technology•Richmond, VA

2d•Onsite

About The Position

The QA Engineering Lead is the senior hands-on quality engineer for the Unboxed platform and is personally accountable for the quality of what ships to enterprise clients. This is primarily an individual contributor role: the Lead spends most of their time in the product, designing and executing test strategy, running manual and automated testing, owning release verification, and diagnosing defects. Quality spans four surfaces: a robust learning management system, AI-generated roleplay and practice, coaching workflows, and client-facing analytics and reporting. The role also includes directly managing two full-time QA Engineers with a coaching-first approach and partnering with contract engineering and QA teams to establish and maintain their ways of working. The role owns the quality signal used to decide whether a release is ready.

Requirements

Deep hands-on QA engineering skill: test design, exploratory testing, regression strategy, and defect diagnosis in B2B SaaS. This is the primary skill the role is hired for.
Test automation proficiency and the judgment to know where automation pays off versus where it becomes maintenance burden.
Practical experience testing AI/ML or non-deterministic features, including how to evaluate scored outputs where there is no single correct answer.
Fluency with quality metrics and the ability to use them to drive decisions, not just report them.
Experience establishing and maintaining process in partnership with contract or vendor engineering and QA teams.
Ability to lead a small team while remaining primarily hands-on, and to communicate quality risk credibly to both technical and non-technical stakeholders.
5+ years of QA or quality engineering experience in B2B SaaS, with demonstrated ownership of test strategy and release quality.
A track record of staying hands-on as a senior IC.
Experience mentoring or leading other QA engineers and partnering with contract or offshore teams on process and ways of working.
Hands-on experience with test automation frameworks and modern CI/CD testing practices.
Experience testing AI-driven or data-driven features, or a clear ability to reason about quality under output variability.
Familiarity with enterprise quality expectations.
Experience with Agile/Scrum methodologies and tools such as JIRA.
Bachelor’s degree in a relevant field, or equivalent practical experience.

Responsibilities

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.