AI Ops Engineer Marketing

AI platform for creating, deploying, and managing full-stack software through natural-language interaction.

Series CRecently funded0 current maintainers0 active leadsTeam intelligence

Maintainer signals as of 9/25/2026

Stockholm, Sweden
About Lovable

Lovable lets people describe an idea in plain language and collaboratively build production-grade software. Its platform includes hosting, authentication, payments, integrations, security features, and deployment infrastructure.

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Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will work with Marketing to map workflows, systems, data sources, and expert decision points. You will build and launch AI agents and workflows for campaign operations, content, brand guidance, and trusted marketing data. You will define project goals and ownership, establish access rules and runbooks, measure outcomes, and improve or retire systems based on results.

Requirements

  • 6+ years building and shipping production software or data systems
  • Hands-on experience with TypeScript, Python, or SQL
  • Deep marketing knowledge
  • Experience integrating ad platforms, analytics, CRM or CDP, and content tools
  • Experience building with LLMs, agents, and evaluation
  • Product judgment
  • Senior stakeholder management
  • Knowledge of access control and data handling

Responsibilities

  • Map Marketing workflows, systems, data sources, owners, and expert judgment
  • Define project problems, metrics, owners, and completion criteria with Marketing leadership
  • Connect launch context across tickets, documents, Slack, competitive intelligence, and usage data
  • Build agents and workflows for performance and social marketing
  • Encode positioning, messaging, and voice guidance into reusable systems
  • Connect Marketing systems to the shared company data layer
  • Launch systems with owners, runbooks, access rules, and review cadences
  • Measure results and improve, extend, or retire systems
  • Bring product gaps from internal use to product teams