Lifecycle Marketer Self-Serve
AI platform for creating, deploying, and managing full-stack software through natural-language interaction.
Maintainer signals as of 9/25/2026
Funding history
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.
Skills
About the Role
You will operate lifecycle marketing for the self-serve base, covering activation, engagement, retention, and reactivation. You will design adaptive lifecycle programs that determine the right audience, timing, channel, and content based on behavior and context. You will apply AI and automation to content generation, personalization, segmentation, decisioning, and analysis. You will build experimentation and data-driven optimization into lifecycle programs, measure incremental impact, and partner with Data, Product, and GTM teams to deliver timely, valuable messaging.
Requirements
- Have 5+ years of experience in B2C lifecycle, CRM, or growth marketing at consumer or PLG scale.
- Have 3+ years of hands-on expertise with a modern lifecycle marketing platform such as Braze, Iterable, or Customer.io.
- Be fluent in Liquid templating, email HTML/CSS, segmentation logic, and event-driven campaign architecture.
- Have experience building adaptive, evolving lifecycle systems.
- Have hands-on experience applying AI and automation to content creation, personalization, segmentation, and decisioning logic.
- Demonstrate content craftsmanship that supports Lovable’s brand.
Responsibilities
- Operate lifecycle marketing for the self-serve base across activation, engagement, retention, and reactivation.
- Serve as the lifecycle point of contact for product launches, experiments, and GTM moments.
- Design intelligent lifecycle programs that determine audiences, timing, channels, and content based on behavior and context.
- Apply AI and automation to content generation, personalization, segmentation, decisioning, and analysis.
- Build experimentation and data-driven optimization into lifecycle programs and measure incremental impact.
- Partner with Data, Product, and GTM teams to deliver native, timely, and valuable lifecycle messaging.
