AI Platform Engineering Manager

What you’ll own

• →Infrastructure. Proxmox clusters, AWS workloads, self-hosted services (SSO, wikis, observability, internal apps). You decide the architecture, you ship the IaC, you own the runbooks.
• →Internal apps and agents. When a venture needs an internal tool, dashboard, ai agent, or workflow automation, your team scopes it, builds it, and ships it. You write code on this team, not just review it.
• →AI workflows across the group. Every venture has its own AI needs. You partner with the lead of each, scope what they need, design the workflow, and ship it. You are the person every department head comes to when they want AI in their work.
• →IT operations. Identity, endpoint management, access reviews, the unglamorous reliability work that keeps 150 people productive.
• →The translation layer. Stakeholders bring you problems in plain English. You turn them into technical specs your team can ship.

You’ll lead three direct reports today: one each for IT, infrastructure, and tools/apps. The team grows from there based on what the ventures need.

The operating model is AI-native. You will work alongside an AI DevOps agent that maintains runbooks, proposes architecture, and reviews infrastructure changes. Claude or Cursor are daily tools for you and your team, the same way an IDE is. Infrastructure is code by default. Documentation is written as work happens, not after. If the idea of pairing with an AI agent on architecture review is interesting rather than uncomfortable, you’ll fit the room.

• 5-10 years of experience. Where you started as a developer, moved into DevOps or platform engineering, and never stopped writing code. You’ve been doing this long enough to have opinions about what works.
• You’ve managed small teams (2-5 people) and were good at it, but the management didn’t pull you out of the work.
• You have excellent organizational discipline. Drift is your enemy. SOPs, runbooks, and documentation stay current because you keep them current, not because someone reminds you.
• You communicate clearly across functions. You can sit with the head of sales, the head of finance, or the head of operations, listen past the stated problem to the real one, and walk out with a working spec.
• You already use AI coding tools in your daily work, not because someone told you to, but because you tried them and they made you better.
• You’re comfortable owning ambiguity. Nobody hands you a roadmap. You build it.

You’re not a fit if

• You haven’t shipped code in years and prefer it that way.
• You’re a deep specialist (pure SRE, pure observability, pure security) who wants to go deeper into one layer.
• You need a fully scoped backlog before you can start.
• You let documentation rot. You think SOPs are someone else’s job.
• AI in your daily workflow feels like noise rather than amplification.