Tactical Edge
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QA Engineer

Ensure enterprise AI platforms and solutions are reliable, tested, and production-ready.

Remote / HybridSecurity, Quality & ReliabilityFull-time

Role Overview

The QA Engineer is responsible for ensuring Tactical Edge's AI platforms and customer solutions meet high standards of quality and reliability before and after deployment. The role collaborates closely with engineering, product, AI, and delivery teams to identify risks early, define test strategies, and ensure systems behave predictably in production.

What You'll Do

  • Define and execute test strategies for platforms and AI-powered solutions.
  • Validate functional, integration, and regression behavior across systems.
  • Collaborate with engineering and product teams early in the development lifecycle.
  • Identify edge cases, failure modes, and risk areas in complex systems.
  • Contribute to test automation, tooling, and quality processes.
  • Support release readiness and production validation.
  • Analyze issues from production and help prevent regressions.
  • Continuously improve QA practices and documentation.

    • What We're Looking For

  • Experience in QA for production software systems.
  • Strong understanding of testing methodologies and quality practices.
  • Ability to think in terms of systems, workflows, and edge cases.
  • Comfort working with developers, product managers, and delivery teams.
  • Attention to detail combined with pragmatic judgment.
  • Familiarity with test automation and CI/CD pipelines.
  • Bonus: Experience testing AI-driven, data-heavy, or distributed systems.

    • How We Work

    Outcome-driven

    Reliable systems over rushed releases

    Enterprise-first

    Quality, trust, and predictability

    Quality by design

    Early involvement, not late fixes

    Small teams, high ownership

    Autonomy with accountability

    What You'll Get

    • Ownership of quality for production AI systems
    • Exposure to enterprise-scale platforms and deployments
    • Cross-functional collaboration with product, AI, and engineering teams
    • Competitive compensation (role/location dependent)
    • Flexible work setup where applicable

    Hiring Process

    1. 1Intro call (context + fit)
    2. 2QA scenario discussion (testing strategy for a real system)
    3. 3Cross-functional interview (engineering/product perspective)
    4. 4Final conversation

    We value thoughtful testing, early risk detection, and clear communication.

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