Director, Lifecycle Marketing

About the Opportunity

Lifecycle marketing at OKX is evolving. We're not looking for someone to run campaigns — we're looking for someone to fundamentally rethink how we engage traders across the US market on one of the world's leading crypto platforms.

This is a leadership role for a marketer who thinks in systems, not sends. Someone who is comfortable defining a US-market engagement strategy as well as getting into the work to make it happen. Reporting to the Global Head of Lifecycle Marketing, you'll help define the vision, strategy, and output of lifecycle marketing for the US. Your execution layer is AI agents, cross-functional partners, and co-operating with the broader Lifecycle marketing team. That means your ability to train, direct, brief and critique is as important as your ability to set direction.

If your default mode is execution and program management or pure strategy and handoff, this isn't the role for you. If your default mode is leading from the front, and you have the craft and judgment to shape the work through strategic problem-solving, AI-native thinking, and a relentless focus on what quality looks like to actually move users — read on.

What You’ll Be Doing

• Lifecycle Strategy & Vision Define how OKX engages US users from acquisition through activation, retention, and reactivation — across segments and products. You'll set the strategic framework for the US market, working in close alignment with the Global Head of Lifecycle to ensure regional strategy ladders into global priorities. This means deeply understanding US crypto user behavior, identifying the highest-leverage moments in the lifecycle, and building programs that compound over time.

• AI-Native Ways of Working You will lead by example in embedding AI into every layer of lifecycle marketing — from ideation and content development to segmentation, testing, and analysis. Critically, this includes building and training agentic AI workflows: multi-step, autonomous systems that execute lifecycle programs at scale. You'll know the outcomes of poorly trained agents. You won't just adopt AI tools; you'll help determine which ones we build, which we leverage for each task, and how we use them to raise the ceiling on what a lean, high-performing team can deliver.