Agentic Operator, Growth Marketing
Ramp
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Compensation
Salary & market context
167% above the BLS national median
BLS national median: $74,680
- $10,000
Requirements
Top requirements
- You have strong opinions on tool-use vs. code-gen agents, when to use RAG vs. fine-tuning, and how to build evals that actually matter. - Think in systems and loops and not tasks and tickets.
- NICE TO HAVES - Familiarity with marketing systems like HubSpot, Segment, Amplitude, Salesforce, similar GTM platforms, or a willingness to learn. - You've built multi-agent systems with orchestration layers and inter-agent communication. - You've shipped internal tools or platforms that other teams actually adopted and relied on.
Perks & setup
Benefits candidates care about
- BENEFITS (FOR U.S.-BASED FULL-TIME EMPLOYEES) - 100% medical, dental & vision insurance coverage for you - Partially covered for your dependents - One Medical annual membership - 401k (including employer match on contributions made while employed by Ramp) - Flexible PTO - Fertility HRA (up to $10,000 per year) - Parental Leave - Unlimited AI token usage - Pet insurance - Centralized home-office equipment ordering for all employees - Health and Wellness stipend - In-office perks: lunch, snacks, drinks, and more - Budget for intra-office travel - Relocation support to NYC or SF (as needed) REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.
Why candidates care
Benefits & perks
- BENEFITS (FOR U.S.-BASED FULL-TIME EMPLOYEES) - 100% medical, dental & vision insurance coverage for you - Partially covered for your dependents - One Medical annual membership - 401k (including employer match on contributions made while employed by Ramp) - Flexible PTO - Fertility HRA (up to $10,000 per year) - Parental Leave - Unlimited AI token usage - Pet insurance - Centralized home-office equipment ordering for all employees - Health and Wellness stipend - In-office perks: lunch, snacks, drinks, and more - Budget for intra-office travel - Relocation support to NYC or SF (as needed) REFERRAL INSTRUCTIONS If you are being referred for the role, please contact that person to apply on your behalf.
Start here
Requirements
- You have strong opinions on tool-use vs. code-gen agents, when to use RAG vs. fine-tuning, and how to build evals that actually matter. - Think in systems and loops and not tasks and tickets.
- NICE TO HAVES - Familiarity with marketing systems like HubSpot, Segment, Amplitude, Salesforce, similar GTM platforms, or a willingness to learn. - You've built multi-agent systems with orchestration layers and inter-agent communication. - You've shipped internal tools or platforms that other teams actually adopted and relied on.
Responsibilities
What you'll do
- If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it.
- This isn't a role where you use AI to work faster, it's a role where you build AI that does the work and recursively learns.
- You'll take marketing workflows - content production, lead enrichment, campaign ops, etc. - and break them down into agent architectures: skills, tools, evals, memory, and orchestration layers that run 24/7 and get better on their own.
- WHAT YOU’LL DO - Build AI agents from scratch that autonomously run marketing workflows: content generation, campaign development and launches, paid channel optimization, creative testing, and more. - Break down workflows into the pieces agents actually need: skills, tools, evals, guardrails, memory, and feedback loops.
- You'll care a lot about getting this decomposition right. - Build evaluation frameworks that measure agent quality, catch regressions, and drive improvement without someone babysitting the system. - Design self-improving loops.
- Agents should monitor their own outputs, learn from outcomes, and get sharper over time.
Role snapshot
About the role
ABOUT RAMP
Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $100B in annualized spend flows in and out of 50,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books.
The problems are high-stakes, data-dense, and unforgiving.
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