Jobs · Business Development · New York

AI Solutions Strategist

Ramp · New York, NY · 3 wk ago
HybridBusiness DevelopmentFull-time

About the role

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.

What You'll Do

  • Discover and diagnose customer needs
  • Run stakeholder interviews and workflow deep dives with Finance, Procurement, AP, and IT teams
  • Map end-to-end processes and pinpoint the “why” behind pain points (risk, cost, cycle time, compliance, exceptions)
  • Identify where AI can create leverage, including intelligent intake, classification, routing, matching, and exception handling
  • Translate needs into clear solution requirements
  • Define deployment plans that balance speed, safety, and scalability (MVP → iteration → rollout)
  • Partner with customer teams to align on change management, operating model updates, and adoption plans
  • Partner with technical teams to implement AI-powered workflows
  • Work closely with Ramp Engineers and AI builders to design and ship solutions that meet real customer workflows
  • Define data inputs, integrations, and governance needs (system-of-records, policy rules, auditability)
  • Support evaluation of models and prompts against customer-specific edge cases and risk tolerance
  • Drive feedback loops into Ramp’s core product
  • Synthesize learnings across customers into reusable patterns and product opportunities
  • Write high-signal briefs for Product and Engineering: what customers need, why it matters, and what to build next
  • Advocate for scalable solutions that reduce custom work over time
  • Communicate impact and guide executives
  • Present status, outcomes, and recommendations to audiences ranging from operators to execs
  • Quantify impact (time saved, error reduction, improved compliance, faster close) and connect it to business outcomes
  • Create simple narratives, demos, and artifacts that make AI workflows understandable and trustworthy

What You Need

  • 4+ years of relevant experience
  • Strong customer empathy and the ability to earn trust quickly with senior stakeholders
  • Excellent problem framing: you can turn messy workflows into clear systems and priorities
  • Ability to operate in ambiguity and iterate quickly while keeping quality high
  • Able to communicate clearly in writing (briefs, requirements, postmortems) and verbally (workshops, exec readouts)
  • A builder mindset: you like shipping, learning, and improving the system
  • Experience in solutions, implementation, product strategy, consulting, or technical program management
  • Strong grounding in corporate finance / controllership workflows, including accounting close, spend governance/controls, budgeting, procurement, and AP operations
  • Experience translating finance requirements into system design and configuration (e.g., ERP/accounting, procurement, expense management, payments), including integrations, data mapping, and controls
  • Ability to partner with finance system owners/admins to drive change management, testing (UAT), and successful rollouts
  • Familiarity with finance operations workflows (AP, procurement, expenses, cards, accounting close)
  • Exposure to AI-enabled products, automation, or applied ML (you do not need to be an ML engineer)
  • Basic comfort with data concepts and systems integration (APIs, ETL, SQL, spreadsheets, data quality)

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