Full-Time
Quality Assurance Engineering Lead
Future Secure AI
201-500 employees
Delivers persona-based, multi-agent enterprise AI Co-Workers
Compensation Overview
CA$135k - CA$155k/yr
Austin, TX, USA
In Person
Bachelor's
 Engineering Management (1) |
|---|
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- A bachelor's degree in Computer Science, Information Systems, or a related field is required.
- At least 6 years of experience in software quality assurance is required, including at least 2 years directly managing a quality assurance team.
- Experience operating as both a manager and an individual contributor while remaining technically hands-on is required.
- Strong proficiency in manual and automated testing is required, including hands-on experience with Selenium, JUnit, and TestNG.
- Experience with continuous integration and continuous delivery tooling and integrating quality assurance into deployment pipelines is required.
- A solid understanding of Agile and Scrum methodologies is required.
- People leadership skills, including hiring, mentoring, conflict resolution, and performance management, are required.
- The ability to translate quality risk for technical and non-technical stakeholders is required.
- The ability to prioritize and switch between strategic and hands-on work in a fast-paced environment is required.
- Build and grow the quality assurance team, including hiring, onboarding, and setting performance expectations.
- Manage day-to-day team operations, including workload distribution, one-on-one meetings, performance reviews, and career development.
- Personally execute hands-on functional, regression, performance, and security testing on priority features or releases.
- Own the quality assurance strategy and roadmap, aligning testing priorities with product and engineering goals.
- Design and maintain test plans and work directly with development teams to ensure requirements are covered.
- Drive adoption of automation frameworks and tooling to improve testing efficiency and reduce manual overhead.
- Own quality assurance integration into continuous integration and continuous delivery pipelines and partner with DevOps to optimize test execution and feedback loops.
- Track and report quality metrics, including defect escape rate, test coverage, and release readiness, to leadership.
- Lead root-cause analysis on significant quality escapes and drive process improvements.
- Represent quality assurance in cross-functional planning and architecture reviews and advocate for testability and quality standards.
Future Secure AI builds persona-based, multi-agent AI Co-Workers designed for large enterprises and private equity firms. Their core offering, Red-Zone AI Co-Workers, consists of over 100 agent personas that automate complex, high-stakes workflows. The agents integrate with a client’s core systems and governance frameworks and operate securely on the client’s network, remaining cloud- and LLM-agnostic to avoid vendor lock-in. Workflows run within a hybrid team, with AI Co-Workers reporting to human managers and maintaining human-in-the-loop oversight. The company differentiates itself by targeting mission-critical environments with on-premise deployment, strong governance, and integration into existing IT and security controls, rather than generic AI tools. Their stated goal is to deliver 10x to 20x ROI on operating costs, often paying for themselves within six months. Clients span infrastructure, services, finance, health, and connected economies.
Company Size
201-500
Company Stage
N/A
Total Funding
N/A
Headquarters
N/A
Founded
N/A
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Simplify's Take
What believers are saying
- September 2026 jobs board lists 48 openings, showing aggressive delivery and security hiring.
- Future Secure AI cites first wins in finance, tax, healthcare, and private equity.
- HQ relocation and U.S. expansion target accelerating demand across Austin, New York, Toronto.
What critics are saying
- Microsoft, Palantir, and ServiceNow can bundle similar agents into existing enterprise contracts.
- AFR reported a planned 2027 IPO; public-market scrutiny will expose retention and margins.
- If Fortune 500 buyers standardize on one model stack, Future Secure AI loses differentiation.
What makes Future Secure AI unique
- Austin HQ and Todd Hewlin signal enterprise-scale execution from March 2026 onward.
- On-network, LLM-agnostic deployments reduce model lock-in for regulated buyers.
- Persona-based Red-Zone AI targets mission-critical workflows, not generic chatbot automation.
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Benefits
Flexible Work Hours