QA Engineering Lead

Unboxed Training & Technology

QA Engineering Lead for Unboxed platform quality assurance. Managing test strategy, overseeing QA Engineers, ensuring release quality for enterprise clients.

Posted 7/29/2026full-timeRichmond • Virginia • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in end-to-end test strategy execution, quality measurement for AI-driven features, and effective collaboration with engineering teams to ensure high-quality deliverables. Proven ability to mentor QA engineers and maintain rigorous quality standards across both in-house and contract contributions.

Highest-signal resume keywords

Test Strategy OwnershipTest Automation FrameworksAI Quality EvaluationAgile/Scrum MethodologiesMentoring QA Engineers

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Quality AssuranceTest AutomationRegression TestingExploratory TestingDefect Severity RubricAcceptance Criteria DefinitionQuality Metrics ReportingAI-Driven Feature TestingCI/CD Testing PracticesB2B SaaS Experience

Soft Skills

CoachingCollaborationCommunicationLeadershipProblem-Solving

Tools & Technologies

JIRACI/CD ToolsTesting FrameworksMonitoring ToolsDefect Tracking Systems

Industry Keywords

B2B SaaSQuality EngineeringAgileEnterprise Quality ExpectationsClient Trust

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

Competitive salary and benefits
Ample paid time off
Dynamic and convenient office location – unlimited snacks, casual dress code, covered parking and gym on site
Open communication and a commitment to fostering teamwork across the organization