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Lovable is seeking an AI Ops Engineer to own internal AI systems and automation infrastructure that enable the company to operate at scale. You'll be part of Project Automate Lovable, working with the AI Operations & Automation and FBOS teams to define how AI-native companies operate internally.
In this role, you'll design and build workflow automations, internal AI tools, and data enrichment pipelines that allow a 200-person team to move with the velocity of a much larger organization. You'll use Lovable itself as a primary building tool, leveraging AI agents, no-code platforms (n8n, Clay), and raw code as appropriate.
Key responsibilities include: owning end-to-end internal AI systems from conception through maintenance; connecting and enriching company data across the tech stack (Slack, Linear, Notion, Ashby, etc.) to power automations and decision-making; deploying AI agent armies with Claude/ChatGPT and MCPs so every teammate has AI working for them; turning fragmented data into reliable, usable systems; and leveling up the entire team to become AI power users.
You'll need shipped production automation experience at scale—business-critical systems that ran without constant oversight. You combine an engineering mindset with modern tooling fluency, understand APIs and databases, and can review code confidently. Data modeling, complex SQL, and pipeline design are in your wheelhouse. You're obsessed with testing new AI tools and models, have deployed internal AI systems before, and can't ignore inefficiency once you spot it. High agency is essential: you find bottlenecks, build fixes, and ship without waiting for permission.
Lovable is a generational AI company founded in November 2024, recognized by TIME as one of the 100 Most Influential Companies and featured on Forbes AI 50 and CNBC Disruptor 50. The platform has powered over 60 million projects from solopreneurs to enterprises like Adidas and Zendesk. The team is small, talent-dense, and moving quickly, with a culture rooted in extreme ownership, high velocity, and low-ego collaboration.
