Engineering Leader, Platform Engineering

- Own Platform's company-level objectives and the engineering plan that delivers them.

- Translate company priorities and product-engineering needs into a platform roadmap, in a way that flows both up and down.

- Be responsible for build-vs-buy and architecture-level trade-offs across infrastructure, data, developer experience, and AI tooling; own the technical roadmap and how it balances against the needs of your customers.

- Represent Platform and collaborate with cross-functional leadership partners and in engineering-wide leadership conversations.

- Coach EMs to a higher bar with clear feedback, growth plans, and direct support.

- Drive AI-native development in line with ClassDojo's engineering practices (flow-based delivery, vertical slicing, WIP discipline, Definition of Done, observability)

- Address performance issues early and clearly; develop managers out of "fine" performance into great performance.

- Be directive when our values, quality bar, or ways of working are at stake.

- Treat the product engineering areas as customers: understand their needs, measure adoption and satisfaction, and prioritize accordingly.

- Build paved roads and golden paths that teams want to use; earn adoption rather than mandating it.

- Take accountability for SLAs/SLOs and incident response across the platform surface.

- Make tech-debt and reliability trade-offs on purpose, not by accident.

- Support and drive architecture and systems design decisions across infrastructure, data, DevEx, and AI tooling; ensure systems are reliable, maintainable, and operationally ready.

- Make build-vs-buy calls deliberately; avoid both not-invented-here and unmanaged sprawl.

- Co-own the platform roadmap and quality bar with the product engineering leads who depend on you.

- Partner with Security, Ops, Data, and other functions as the platform requires.

- Build pragmatic interim solutions that work today and migrate cleanly as platform capabilities mature.

- 2+ years managing managers, with direct reports who were themselves people managers.

- 10+ years total in technical roles, with a strong individual-contributor era you can still draw on.

- Have owned a platform, infrastructure, data, or developer-productivity area and delivered a measurable outcome (throughput, reliability, cost, or operational safety).

- Have built or evolved platform engineering practices across multiple teams, not just within one, and earned adoption.

- Comfortable making and defending build-vs-buy and architecture-level trade-offs across the platform surface; can still reason about code with taste.

- Embrace Candor > Harmony : give the hard message early, comfortable with disagreement.

- Use LLM-based tools daily and push your teams to adopt them.

- Are an excellent written communicator; can articulate strategy and trade-offs clearly in writing.

- Experience running infrastructure, data, DevEx, or AI platforms at meaningful scale.

- Has built developer platforms that internal engineers genuinely adopted (paved roads, golden paths, internal developer platforms).

- Has used AI-native workflows to materially change how a team designs, ships, and operates, and/or has built AI tooling/platform for other engineers (not just personal use).

- Experience leading a remote-first, distributed engineering team.

- Brings a network of high-quality platform/infrastructure engineering talent.