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Ramp

Mid

Ship the AI agents and tools that run Ramp's customer experience motion

Ramp is hiring a hands-on PM/builder to own how AI transforms both customer-facing agentic products and internal CX operator tooling, reporting to the Head of Operations and AI. This is an execution role — prototyping and shipping AI agents, defining eval frameworks, and partnering with engineering on AI data reliability — not a strategy-deck role. Expect the interview to test real AI-building fluency (coding harnesses, LLM concepts), operational empathy across CX/sales/finance/risk, and a bias toward shipping over planning.

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What this interview tests

  • Hands-on AI agent/product building (not roadmap-only PM work)
  • Working knowledge of LLM concepts (prompting, fine-tuning, embeddings, retrieval, evals)
  • Fluency with AI coding harnesses (Cursor, Claude Code, Codex) for prototyping
  • Designing eval frameworks, QA checks, and dashboards for AI agent performance
  • Defining the human-operator/AI-agent division of labor in a CX motion
  • Operational empathy across CX, sales, finance, and risk teams

Common question themes

Tell me about an AI-powered tool or agent you personally prototyped and shipped at scale

How would you design an eval framework to measure whether a customer-facing AI agent is performing well?

How do you decide what work should go to an AI agent versus a human operator in a CX workflow?

Walk me through your fluency with a coding harness like Cursor or Claude Code — how have you used it to ship something real?

How would you partner with CX, finance, and risk teams to identify and solve an operational pain point with AI?

Describe a foundational or unglamorous AI infrastructure problem you tackled rather than a flashy feature

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