AI Ops Engineer (Marketing)

Job description

**TL;DR:** We are looking for a senior engineer with deep marketing knowledge to join Applied AI, the team that rebuilds how Lovable operates as a company. You will work embedded with Marketing and build the AI systems, data, and agents that its teams run on. You will ship production software yourself, on Lovable, with the Applied AI engineers. ## **Why Lovable?** Lovable is the software creation platform that gives people the power to act on the problems closest to them. For decades, turning an idea into software required so much capital, technical fluency, and time that many ideas never came to life. Lovable is the counterargument: a platform for all people with ideas, ambition, and problems worth solving. From solopreneurs to small business owners to teams at companies like Adidas and Zendesk, people have built over 60 million projects on Lovable since its launch in November 2024. And we’re just getting started. We’re building a generational company from Stockholm, with growing teams in London, Boston, New York, and San Francisco. Our team is small, talent-dense, and moving quickly, with a culture rooted in extreme ownership, high velocity, and low-ego collaboration. We look for people who care deeply, ship fast, and are eager to make a dent in the world. Lovable is one of TIME’s 100 Most Influential Companies and has been recognized on the Forbes AI 50 and CNBC Disruptor 50, reflecting our momentum as one of Europe’s fastest-growing AI companies and one of the most ambitious places to build in this next era of software. ## **What we're looking for** - 6+ years building and shipping production software or data systems that people depend on. Recent hands-on work in TypeScript, Python, or SQL. - Deep marketing knowledge from a marketing organization, a MarTech company, or a product or data role serving marketing teams. You know how paid and social channels, attribution, CRM, content, and positioning work in practice and where they break. - Experience integrating marketing systems: ad platforms, analytics, CRM or CDP, and content tools. You know their APIs and data well enough to build on them. - Experience building with LLMs: agents, evaluation, and the judgment to know where a rule-based system does the job better. You can test the quality of model output and make it reliable enough for daily use. - Strong product judgment. You start from the problem, choose priorities with the people affected, and improve a system through use and feedback. - Senior stakeholder skills. You work directly with the CMO and Marketing leads, form your own view, and disagree in writing with a better path attached. - Care for permissions and data handling. Marketing systems touch customer data and spend. You treat access control as a design requirement from day one. - Comfort building on a high-level platform. We build our internal systems on Lovable itself. Bespoke infrastructure needs a written reason. ## **What you'll do** - Run a listening tour with Marketing. Map current work, systems, data sources, owners, and the places where expert judgment lives. Propose builds only after that. - Agree each project with Marketing leadership up front: the problem, the metric, the owner, and the definition of done. - Connect the context a launch depends on: Linear tickets, internal docs, Slack threads, competitive intel, and usage data. When the scope changes, the change propagates to every asset that mentions it. - Build agents and workflows for Performance and Social: creative variants, campaign setup, and quality checks against brand guidance, with human review where spend or brand is at stake. - Encode Brand and Product Marketing judgment into systems: positioning, messaging, and voice guidance that other teams and agents apply without a meeting. - Connect Marketing's systems to the shared company data layer so agents and workflows can act on trusted data. - Build on the shared Applied AI foundation and contribute back. Reuse company data contracts, permissions, and agent patterns. Extract what Marketing needs into reusable pieces. - Launch every system with a named owner, a runbook, access rules, and a review cadence. Teach the Marketing team to operate it without you. - Measure results with Marketing and use them to decide what to improve, extend, or retire. - Bring concrete product gaps from internal use to Lovable's product teams. ## **How the role fits** You report into Applied AI and spend most of your time with Marketing. Marketing leadership sets the priorities and owns the results. You agree with them on what to build, how to measure it, and who owns each system once it runs. Applied AI owns the shared foundations you build on: company data contracts, permissions, the information architecture and reusable agent patterns. You work day to day with the Applied AI engineers and with colleagues embedded in Sales, Finance, People, and Support. A capability you build for Marketing often becomes a building block for another function, and the reverse is true too. ## **Our tech stack** We build with tools that both humans and AI love. - **Platform:** Lovable itself, Supabase (PostgreSQL), Cloudflare - **Languages:** TypeScript, Python, SQL, Go - **AI:** Anthropic, OpenAI, MCP, AI agents - **Data:** BigQuery - **Marketing systems:** the ad platforms, analytics, and CRM tools Marketing already uses **About your application** Please submit your application in English. It's our company language, so you'll be speaking lots of it if you join. We treat all candidates equally - if you're interested, please apply through our careers portal.