AI Operations Specialist | Enablement

Ramp•New York, NY

About The Position

As an AI Product Operator, you will help accelerate Ramp’s goal of becoming the most productive company in the world through AI. You will boost not just AI usage across our business, but an AI-first mindset—so that every team develops a muscle for leveraging new AI capabilities instinctually, and is enabled to act on those instincts. Part vibe coder, part data expert, part product manager, and part business ops maven, you’ll work across disciplines and co-develop the cutting edge of AI building technology for non-engineers, and use it to drive massive change at high velocity.

Requirements

2–5 years in product management, product ops, BizOps, strategy, technical program management, revenue operations, or similar.
Deep and demonstrated experience using AI to build, ship, and transform work in prior teams or projects.
Technical fluency with low-code/no-code and development copilot tools (Notion, n8n, Gumloop, Cursor, Claude Code), SQL and BI tools, APIs, scripting, or integrations.
Operational empathy: able to partner with business teams to deeply understand challenges and deliver rapid solutions.
Strong communicator: you can write crisp docs (with AI!) and run persuasive, engaging internal training sessions that have lasting impact.
Self-starter with high ownership, comfortable with autonomy and ambiguity.

Nice To Haves

Familiarity with departmental workflows in operating teams - Sales, CX, Finance, Risk, HR, etc.
Prior experience in internal enablement or change management programs.

Responsibilities

Deploy dozens of AI-driven automations or copilots across a focused set of non-engineering Ramp teams within 6–12 months.
Enable hundreds of Ramp team members with >90% active usage of deployed workflows in their daily work.
Map processes, build workflows using tools like Gumloop, n8n, Notion, Cursor, or ChatGPT plugins, and orchestrate integrations.
Measure impact via dashboards, QA checks, and iteratively optimize based on user feedback.
Seed an AI-native culture, coaching internal “AI champions” and embedding templates and practices into team norms.