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About the Role
As an AI Solutions Strategist, you will sit at the intersection of customers, AI delivery, and Ramp’s core product teams. You will partner with enterprise/strategic customers to deeply understand their finance workflows—especially corporate finance and controllership priorities like close, controls, and spend governance—identify high-impact opportunities for AI and automation, and translate those needs into clear problem statements, solution designs, and actionable feedback for Ramp’s Product, Engineering, and Go-to-Market teams.
This role is for someone who can listen carefully, structure ambiguity, and turn on-the-ground learnings into scalable solutions. This role required high proactivity and bias to action.
What You'll Do
No two days are the same, but you can expect to
- 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
- Turn qualitative input into crisp requirements: problem statements, success metrics, constraints, and acceptance criteria.
- 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.
- Help specify 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
- 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.
- Comfort operating in ambiguity and iterating quickly while keeping quality high.
- Ability 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).
Working styleWe collaborate best when we’re close to the work and close to each other. This role is hybrid in New York, with time in-office to partner tightly with product and engineering teams. Importantly, this role required spending time with customers to understand real workflows, so travel and flexibility are critical to success.
