New York, NY (HQ), NY, USA (United States) · Remote
Full-time
Mid level
5 months ago
Verified apply link — checked 4 hours ago
Salary undisclosed
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 $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE At Ramp, people are the single biggest lever on our trajectory, and the bar for who joins this team gets higher every quarter, not lower. We're hiring a Recruiter who treats recruiting as a research discipline as much as a relationship one: someone who can map a market, identify the operators who'll outperform their peers, and run a full-cycle process that wins them. You'll own end-to-end hiring across Sales and GTM functions, from first conversation through offer close, and partner with GTM leadership to translate ambitious hiring plans into real teams. The recruiters who do this best at Ramp combine craft on the front end (research, identification, calibration) with execution on the back end (closing, candidate experience, pipeline discipline). We're looking for both. WHAT YOU'LL DO - Use AI and research to find top talent. You'll build target lists of high performers at peer and aspirational companies using LinkedIn Recruiter, Sales Navigator, Gong signals, internal data, and AI tools like Claude. We expect AI to be part of your daily workflow, not a novelty, but a core part of how you identify, qualify, and reach candidates. - Calibrate quickly and map the market. For every new search, you'll develop a clear point of view on what "great" looks like, who fits the profile, and where to find them, then share that POV with hiring managers as a written artifact rather than just a slate of resumes. - Run thoughtful, personalized outreach. The best replies come from outbound that's grounded in real research, a candidate's territory, deal motion, or recent move. We care more about reply rate and onsite conversion than send volume. - Own the full cycle, from first outreach through offer close, including pipeline hygiene in Ashby, stakeholder updates, and offer construction. - Close candidates with competing offers. Many of our strongest GTM hires are weighing multiple options, and you'll partner with hiring managers and leadership to build conviction, sequence references, and run a closing motion that wins on substance. - Be a strategic partner to GTM leaders. Push back when a search is mis-scoped, surface compensation reality early, and translate hiring-manager wishlists into a concrete profile within days. - Deliver an excellent candidate experience that's fair, transparent, and fast. Feedback is honest; offers move in days, not weeks. - Improve how we hire by contributing to process changes, comp benchmarking, employer brand, and how Ramp evaluates GTM talent. WHAT YOU NEED - 5+ years of full-cycle GTM/Sales or G&A recruiting, ideally in a high-growth or top-tier startup environment where the bar was non-negotiable. - A real track record of identifying strong talent, not just running searches that closed. Bring examples of candidates you found, ran a process for, and who became top performers. - Comfort using AI in your day-to-day workflow. You already use LLMs to research candidates, draft personalized outreach, summarize calls, or surface signals from messy data, or you're eager to. We see AI fl
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