Build and iterate on AI-assisted workflows for field communications, content creation, and operational efficiency. Serve as a connector between AMER field teams and cross-functional partners in Marketing, Finance, Partnerships, and Customer Success.

I’ve been seeing the same pattern across a lot of marketing teams: the problem usually isn’t “lack of ideas”; it’s the pileup of small operational tasks that slow execution down. A practical way to reduce that drag is to use AI as a first-pass operator, not a decision-maker. The goal is to speed up repetitive work while keeping humans on strategy, QA, and exceptions. Here’s a lightweight workflow that can work for campaign ops, reporting, lifecycle cleanup, or content production: - Start with one repetitive task that happens weekly or monthly - Break it into clear steps: input, transformation, review, output - Identify what can be templated, summarized, classified, or checked automatically - Use AI to draft the first pass, then have a human verify edge cases - Keep a short checklist for quality control so outputs stay consistent - Log the mistakes you catch; those become the next automation candidates - Measure time saved, not just output volume The biggest win is usually not full automation. It’s removing the first 30 to 60 minutes of friction from tasks that nobody enjoys doing manually. A few examples: - Pull raw campaign data, then have AI summarize anomalies before analysis - Draft lifecycle email variants from one approved brief - Turn a meeting note into task owners and next steps - Scan published content for missing metadata or broken formatting If you want this to scale, keep the workflow narrow. Broad “do all the marketing ops” automation usually creates more cleanup than it removes. Small, bounded processes are easier to trust and improve. What repetitive marketing task has the most obvious room for a human-plus-AI workflow in your team?

Take an AI-first approach to improving workflows by identifying opportunities to automate processes, enhance personalization, and accelerate experimentation. Partner closely with Growth Marketing, Product, Engineering, Data Science, and Analytics teams to translate business needs into scalable technical solutions.