Finite State partners with product security teams, the guardians of our connected world, to create transparency for their connected devices and supply chains. Our platform handles connected devices and embedded systems across all industries, including those found in enterprises, healthcare, utilities, connected vehicles, manufacturing facilities, critical infrastructure, and government entities.

We are a fast-growing series-B company with a fully distributed workforce. Led by a team of seasoned experts, we are a mission-driven team passionate about arming our customers with the actionable insights, critical vulnerability data, and remediation guidance necessary to mitigate product risk and protect the connected attack surface. We are committed to a remote first culture.

QA Engineering Manager

Overview

We are seeking an experienced QA engineering leader to drive quality strategy, execution, and team leadership within an AI-first development organization. This is not a traditional QA management role — we are looking for a hands-on technical leader who can both architect modern quality systems and lead, mentor, and grow a high-performing QA engineering organization.

This is a true “player/coach” role: part technical authority, part people leader. You will be responsible for defining and implementing an AI-first quality engineering strategy while also managing and developing a team of QA engineers and automation specialists.

In our environment, AI is a first-class partner in software creation. The QA Staff/Lead Engineering Manager will define how quality is engineered into the product using automation, AI agents, scalable processes, and strong cross-functional collaboration with Product and Engineering.

If you have deep QA automation expertise, experience leading technical teams, and are excited about redefining quality in an AI-native development lifecycle, we want to talk to you.

What You’ll Do

People Leadership & Team Development

Manage, mentor, and develop a team of QA engineers and automation specialists.
Provide regular coaching, feedback, performance management, and career development support.
Foster a culture of accountability, ownership, collaboration, and continuous improvement.
Partner with Engineering leadership on team planning, hiring, organizational growth, and resource allocation.
Help establish clear role expectations, growth paths, and technical standards for the QA organization.
Lead by example as a hands-on technical contributor while empowering engineers to grow and succeed.
Build an inclusive, high-performing engineering culture focused on learning and innovation.

AI-Driven QA & Automation

Lead a team that is designing and implementing AI-agent-driven QA workflows (e.g., autonomous test generation, regression validation, autonomous testing agents).
Integrate LLM-based or AI-assisted tooling into CI/CD pipelines.
Leverage AI to improve test coverage, defect detection, root cause analysis, and release confidence.
Evaluate and introduce emerging AI QA tooling and frameworks.
Develop strategies for testing AI-based product features (e.g., model behavior validation, output consistency, guardrail enforcement).
Leverage AI to build autonomous QA systems that understand product context and proactively improve quality.

Cross-Functional Quality Ownership

Partner closely with Product to drive outcomes based on acceptance criteria, quality gates, and risk assessments.
Work with Engineering leadership to embed quality earlier in the development lifecycle.
Drive a culture where developers co-own quality and automation.
Lead post-incident quality reviews and implement systemic improvements.
Define and standardize quality processes across squads.Technical Leadership & Quality Strategy

Own the end-to-end QA strategy for an AI-first engineering organization.
Lead the transition from traditional QA practices to AI-driven quality engineering.
Establish quality metrics, SLAs, and measurable standards across the product lifecycle.
Serve as a technical authority on testing architecture, tooling, automation strategy, and best practices.
Drive technical decision-making related to test automation, CI/CD quality gates, release confidence, and AI-assisted testing.
Balance strategic thinking with hands-on implementation and technical problem solving.

Communicate quality trends, risks, and strategic priorities to technical and non-technical stakeholders.

Hands-On Execution

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QA Lead Engineer (AI-First Engineering Organization) at name