Testing & QA Engineer II
On-site QA Engineer II at Torch.AI's Leawood, KS HQ who designs and leads manual and automated test plans across UI, backend services, data pipelines, and end-to-end workflows, building automation (Selenium, Playwright, PyTest) and CI/CD quality gates for the company's AI reasoning infrastructure serving government/defense missions.
- Compensation
- Not disclosed
- Location
- HQ - LEAWOOD, KS 66211
- Work setup
- Not specified
- Seniority
- Middle
- Employment
- Not specified
- Experience
- 4+ years
- Category
- Qa
- Posted
Skills
Must have
- 4+ years of professional QA/testing experience, including implementing or improving QA processes
- Experience writing automated tests using Selenium, Cypress, Playwright, PyTest, JUnit, Postman/Newman, REST Assured, or similar tools
- Hands-on experience planning and executing end-to-end testing across integrated systems
- Familiarity with CI/CD environments, test execution workflows, and automated quality gates (GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps, Docker, Kubernetes, SonarQube, or similar)
- Strong debugging, defect triage, and root cause analysis skills
- Proficiency in at least one programming language sufficient to write test automation scripts
- Ability to lead testing activities, coordinate across technical teams, and communicate quality risks clearly
Nice to have
- Experience with performance testing tools such as Locust or JMeter
- Familiarity with distributed systems, data-heavy applications, microservices, or event-driven systems
- Experience supporting secure deployments or high-side environments
- Experience establishing testing standards, mentoring team members, or driving QA process adoption across teams
- Experience leading RCA sessions, documenting corrective actions, and partnering with engineering teams to prevent defect recurrence
Full description
The world’s most consequential systems need the world’s best builders.
A new era is taking shape. AI is no longer confined to models or interfaces. It is becoming the foundation of how decisions are made across governments, industries, and real-world environments. What matters now is not just access to capability, but how it is applied, controlled, and sustained over time.
Torch.AI builds a government-owned reasoning infrastructure which creates a Reasoning Layer to enable machine reasoning at scale, in environments where it is hardest to achieve and least tolerant of failure. This is not incremental software. It is long-term infrastructure designed to endure, integrate, and evolve alongside the systems it supports.
Not another dashboard. Not another workflow app. Not another black-box model glued to a PowerPoint.
The Reasoning Layer is a modular architecture where data is connected, governed, transformed, represented, fused, reasoned over, and delivered into mission applications and operational workflows. It does not replace systems of record. It enables them to function better together.
The Reasoning Layer is comprised of: ORCUS (ingestion, orchestration, governance), NEXUS (semantic representation, vectorization), HALO (graph-based fusion and reasoning) and various product and capability components deployed for specific customer use cases.
We are seeking candidates who approach problems creatively, are comfortable operating without full clarity, and take responsibility for outcomes, not just implementation.
If you’re driven to strengthen U.S. defense readiness and protect national interests, Torch.AI offers meaningful impact at national scale.
What You’ll Do
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Design, lead, and execute manual and automated test plans across UI, backend services, data pipelines, and end-to-end workflows.
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Implement and improve QA processes that define test strategy, entry and exit criteria, defect triage, RCA practices, reporting, and release readiness.
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Build and maintain automated test suites using tools such as Selenium, Cypress, Playwright, PyTest, JUnit, Postman/Newman, REST Assured, or similar frameworks aligned to mission workflows and delivery priorities.
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Shift testing as early as possible by partnering with product and engineering during requirements, design, sprint planning, and code review.
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Support CI/CD testing stages by maintaining automated jobs, test coverage, and quality gates in tools such as GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps, Docker, Kubernetes, SonarQube, or similar platforms.