AI Ops Engineer (FBOS)

📋 Description

• Own internal AI systems that make Lovable run faster than it should.
• Define how AI-native companies operate: Help build the playbook. What we learn here scales to every
• Build internal tools and workflows: Using Lovable, AI agents, no-code, raw code—whatever gets the
• Turn company data into operational leverage: Connect and enrich data across our stack, then put it
• Deploy AI agent armies: Claude/ChatGPT with MCPs configured so every teammate has AI working for
• Squeeze value from our stack: Make the AI features in Slack, Linear, Notion, Ashby, etc. actually

🎯 Requirements

• Shipped production automations at a company: built workflow systems at scale used by teams.
• Engineering brain, modern toolkit: understand APIs, databases, architecture; review code
• Data is part of your building material: design data models, complex SQL, enrichment pipelines
• AI tool obsessed: deployed internal AI tools; experiment with new models/apps/workflows.
• Can't unsee inefficiency: improve broken processes across the company.
• High agency: identify bottlenecks, build fixes, ship them.