Lovable10 дней назад

AI Ops Engineer (FBOS)

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РЫНОК

26 250 ₽медиана по профессии

AI Researcher · 36 вакансий с указанной зарплатой

5 600половина предложений: 16 785–65 900143 300

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Полная занятостьОфис

Обязанности

01Own internal AI systems that make Lovable run faster than it should
02Define how AI-native companies operate: Help build the playbook. What we learn here scales to every company using Lovable
03Build internal tools and workflows: Using Lovable, AI agents, no-code, raw code—whatever gets the job done fastest. Lovable on Lovable first, always
04Turn company data into operational leverage: Connect and enrich data across our stack, then put it directly to work, powering automations, internal tools, AI agents, decision-making, and proactive workflows across Finance, Business Operations, Legal, etc.
05Deploy AI agent armies: Claude/ChatGPT with MCPs configured so every teammate has AI working for them, not the other way around
06Squeeze value from our stack: Make the AI features in Slack, Linear, Notion, Ashby, etc. actually deliver
07Level up the team: Turn everyone at Lovable into AI power users. Document what works. Scale it
08Own it end-to-end: You build it, you maintain it, you improve it

01Shipped production automations at a company: You've built workflow systems at scale that ran without you. Actual business-critical automations used by teams
02Engineering brain, modern toolkit: You understand how systems actually work (APIs, databases, architecture) and can review code confidently. You move fast by choosing the right tool for the job: AI agents (Cursor, Claude Code etc) when they're faster, no-code (Lovable itself, n8n, Clay, etc.) when it fits, raw code when it's needed
03Data is part of your building material: You can turn fragmented data across tools, databases, and external sources into reliable, usable systems. You’re comfortable designing data models, writing complex SQL, building enrichment and transformation pipelines, and creating the feedback loops that keep data trustworthy over time
04AI tool obsessed: You're always testing the latest models, apps, and workflows before anyone else. You've deployed internal AI tools (Claude/ChatGPT with custom contexts, AI agents, MCPs, etc.) at a company and you're constantly experimenting with new ones
05Can't unsee inefficiency: You see the whole company as one machine. Once you spot a broken process, you can't leave it alone
06High agency: You don't wait for permission. You find the bottleneck, build the fix, and ship it