8am is a professional business platform that empowers client-focused professionals with innovative technology. They are seeking a Quality Engineering Manager to lead a team of Quality Engineers within Agile squads, focusing on quality outcomes and the development of their careers while collaborating with various teams to enhance automation and quality standards.
Responsibilities:
- Lead a team of QEs embedded in Agile squads: hiring, coaching, performance management, and growing your ICs along our QE career ladder
- Manage QE resource allocation across squads: rebalancing coverage as priorities shift, covering for leave or open headcount, and surfacing tradeoffs to Engineering and Product when demand exceeds capacity
- Own the QE practice across the squads your QEs work in, enforce release readiness standards through our quality gates, and keep Qase traceability coherent
- Review test plans authored by your team and raise the bar on coverage, clarity, and maintainability
- Partner with peer QE managers, the Tooling and Automation team, Data Engineering, and Product to identify critical automation paths and build them into the quality gates, balancing the flows customers actually use with the flows we want customers adopting
- Pull in our nonfunctional QE specialists (Data, Security, Performance) where their expertise sharpens coverage for the squads your QEs are in
- Partner with Customer Support and Customer Success to bring customer signal into QE, positioning your team as customer advocates who catch failure modes before they become widespread
- Own post-release quality: driving QE response and root cause analysis when escapes happen, and feeding those learnings back into gates, test coverage, and process
- Enforce existing QE processes and drive continuous improvement. Contribute to Themis, our Python/PyTest/Playwright-based automation framework that implements our quality gates
Requirements:
- 3+ years managing a quality-focused engineering team, with a track record of driving defect leakage or equivalent quality metrics down and sustaining them as the codebase and team grow
- Strong judgment under ambiguity and proactive communication in all directions
- An active view of AI in QE
- Technical breadth and depth in both QE practice and the products you'll cover
- Demonstrated experience leveraging AI tools and technologies to improve workflows, enhance decision-making, or drive innovation