Marketing Engineer
FigmaFigma is growing our team of passionate creatives and builders on a mission to make design accessible to all. Figma’s platform helps teams bring ideas to life—whether you're brainstorming, creating a prototype, translating designs into code, or iterating with AI. From idea to product, Figma empowers teams to streamline workflows, move faster, and work together in real time from anywhere in the world. If you're excited to shape the future of design and collaboration, join us!
The Marketing Engineer, AI Deployment will design and build programmatic go-to-market systems and AI-powered workflows that improve efficiency, impact, and execution across Marketing. This role sits at the intersection of operations, data, and marketing with a focus on turning strategy & manual work into scalable, automated systems.
This is not a traditional operations role. It is a systems-focused role dedicated to building the infrastructure, workflows, and intelligence layers that power a modern, product-informed revenue and efficiency engine across marketing. The ideal candidate is an expert in building interconnected data layers optimized for AI, driving AI adoption, and translating complex business challenges into scalable, automated technical workflows that directly drive revenue and operational efficiency.
Success in this role is measured in three ways: agents live—the count of AI systems you've shipped into real, recurring use by marketers; hours saved—manual work returned to the org and reinvested in higher-leverage problems; and revenue driven—pipeline, conversion lift, or deal velocity directly attributable to what you've built. Everything else flows from those three numbers.
This is a full time role that can be held from one of our US hubs or remotely in the United States.
What you'll do at Figma:
- Identify and define high-impact AI use cases across marketing, taking them from prototype to full deployment
- Coach and partner with marketers to take them from novice to full workflow transformation and self-sufficiency
- Build custom tools, agents, automations, and integrations (APIs, MCP Servers) tailored to each operator's responsibilities—campaign ops, lifecycle, content production, intelligence reporting, and beyond
- Own and evolve a GitHub-managed marketing AI cortex of prompts, skills, context files, and agents. Treat it like a product: versioned, documented, and continuously improved
- Recognize patterns across your cohort and systematically productize what works—tools built for one marketer should become reusable for peers, then the broader org
- Measure what works. Define evaluation criteria, instrument AI workflows, and track adoption
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