Manager, Quality Assurance

Description
Most QA leaders inherit a process and make it a little better. That’s not what we’re hiring for.

Description
Most QA leaders inherit a process and make it a little better. That’s not what we’re hiring for. We’re looking for a Manager, Quality Assurance who can fundamentally rethink how software quality should work in an AI-enabled engineering organization. We already have a QA team, automation, established processes, and a functioning software delivery model. We’re not looking for someone to simply maintain it.

You’ll be responsible for taking our QA organization to the next level — and then continuing to raise the bar after you get there. That means challenging old assumptions about manual testing, regression testing, test case creation, defect triage, release validation, automation maintenance, quality gates, and even the traditional role of QA itself. We believe AI creates an opportunity to dramatically improve how software quality is achieved.

Not by replacing good people or good judgment, but by giving exceptional people far more leverage. We want a leader who sees that opportunity and knows how to turn it into reality. You’ll own RTA’s quality standards and QA processes and be accountable for the quality of our software as measured by clearly defined KPIs. Quality is a shared responsibility across Engineering, and you’ll help build the systems, standards, and practices that make that ownership possible.

Someone Who

What We’re Looking For

• Wants to reinvent QA, not preserve it. You question processes that exist simply because “that’s how QA has always worked.”
• Makes quality measurable. You use meaningful metrics such as escaped defects, repeat defects, defect origin, severity, automation effectiveness, regression cycle time, and time-to-detection to understand where we are improving and where we need to change.
• Sees AI as a force multiplier. You actively look for ways AI can improve test design, code analysis, exploratory testing, defect investigation, automation, risk identification, and release confidence.
• Uses AI as leverage, not a substitute for judgment. You understand where AI can dramatically accelerate the team and where experienced human judgment is still critical. You expect the team to validate outputs, understand what they’re doing, and remain accountable for quality.
• Thinks beyond test execution. You understand that mature quality practices influence requirements, architecture, development, observability, deployment, and production behavior.
• Builds systems that make quality scalable. Your instinct is not to add more testers or more manual steps. It is to improve tooling, automation, feedback loops, and engineering practices.
• Sets a high bar — and then raises it. You are never satisfied simply because a metric improved. You continually ask what “great” looks like next.
• Experiments aggressively. You are comfortable trying new AI tools, workflows, agents, testing approaches, and automation techniques — keeping what works and quickly abandoning what doesn’t.
• Builds and develops a high-performing QA team. You set clear expectations, coach and develop your people, hold the team accountable for results, and help them grow beyond traditional manual testing into automation, analysis, tooling, systems thinking, and engineering.
• Uses data to challenge assumptions. You want evidence that quality is improving, not anecdotes.
• Is comfortable disrupting your own process. If the approach you implemented six months ago is no longer the best answer, you change it.
• Takes ownership. You don’t wait for Engineering leadership to tell you what QA should become. You help define it.

Most importantly, you care deeply about our customers. Our customers rely on Fleet
360 to manage school buses,…