You think in terms of governance, not just features. You understand that identity, access control, audit, and policy aren't compliance checkboxes - they're the trust infrastructure that determines whether enterprises can safely let AI act on their systems. You've built or led systems where getting this wrong has real consequences, and you bring that judgment to every product and architecture decision
You raise the bar on reliability as you scale. You've built strong service ownership models, clear on-call practices, and durable quality bars in fast-growing engineering organizations. You treat reliability and operational excellence as a competitive advantage rather than an afterthought, and you know how to instill that discipline in a team that's scaling quickly
You set technical direction - you don't just execute someone else's. You partner deeply with Product and Design as peers and shape strategy together, but you bring a strong, independent engineering point of view to that partnership. You're comfortable being the person who pushes back on a roadmap when the technical or operational reality demands it
You've scaled engineering organizations through structural change. You've led teams of managers and technical leads through real organizational transitions, not just steady-state growth - shifting operating models, redefining ownership, or integrating new ways of working. You know how to bring a team through ambiguity without losing their trust or their output
You are deeply customer- and stakeholder-oriented. You've worked directly with sales, customer success, and enterprise customers to understand what "enterprise-ready" actually means in practice, and you've made the tradeoffs between enterprise scale and delivery speed. You're a credible, responsive partner to go-to-market teams without letting reactive asks crowd out foundational work
You've driven engineering quality and velocity with data. You've established data-driven approaches to measuring delivery, reliability, and quality, and used them to make real investment tradeoffs rather than to produce a dashboard. You have a point of view on balancing reactive/KTLO work against proactive investment, with mechanisms to keep that balance honest
You are a skilled mentor, coach, and communicator. You have a track record of developing engineers and engineering leaders, and you communicate proactively and clearly, in writing by default, to align technical and non-technical stakeholders on vision, tradeoffs, and results
You lead AI-native engineering, not just AI-native products. You've used AI coding agents and orchestration tools (Cursor, Claude Code, Codex, or similar), and you have a concrete point of view on how they change what "good" engineering practice looks like - code review, on-call ownership, and quality bars all need rethinking when a meaningful share of code is agent-authored. You embed accountability into AI-assisted workflows rather than lowering the bar for velocity, and you expect the same discipline from your teams
You champion efficiency and leverage. At Zapier, your work has a disproportionate impact on the business. You default to AI-first thinking in your own work and your team's, and you build systems and practices that compound impact over time rather than relying on heroics
WHAT YOU'LL BE ACCOUNTABLE FOR
This organization spans identity and access management, audit and compliance infrastructure, admin and asset management tooling, AI/agent governance, and enterprise customer-facing engineering