About the company
Ramp is a financial operations platform designed to save companies time and money. Our all-in-one solution combines payments, corporate cards, vendor management, procurement, travel booking, and automated bookkeeping with built-in intelligence to maximize the impact of every dollar and hour spent. More than 30,000 businesses, from family-owned farms to e-commerce giants to space startups, have saved $2B and 20M hours with Ramp. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables over $55 billion in purchases each year. Ramp’s investors include Thrive Capital, Sands Capital, General Catalyst, Founders Fund, Khosla Ventures, Sequoia Capital, Greylock, and Redpoint, as well as over 100 angel investors who were founders or executives of leading companies. The Ramp team comprises talented leaders from leading financial services and fintech companies—Stripe, Affirm, Goldman Sachs, American Express, Mastercard, Visa, Capital One—as well as technology companies such as Meta, Uber, Netflix, Twitter, Dropbox, and Instacart.
Job Summary
What You’ll Do
📍Architect and ship new AI-native product experiences across Ramp, from 0→1 prototypes to scaled production systems 📍Build LLM-powered agents that autonomously reason through complex workflows 📍Contribute to our evolving AI product stack: prompt orchestration, context engineering, evals, embeddings, and retrieval systems 📍Develop full-stack product surfaces (backend & frontend) that incorporate AI into user experiences 📍Collaborate closely with AI platform, infra, and design to push the capabilities of our internal and external tooling 📍Stay on the bleeding edge of the AI ecosystem (tools like Claude Code, Cursor, OpenAI Agent SDK, MCPs, etc.) and identify where and how we can adopt emerging techniques 📍Influence Ramp’s broader AI product strategy and technical vision
What You'll Need
📍2+ years of software engineering experience, including time spent building production-grade full-stack systems 📍Demonstrated experience building AI-powered product features 📍Fluency with modern LLM platforms and AI-assisted engineering tools (e.g., Cursor, Claude Code), with a bias toward rapid experimentation and a working knowledge of prompt engineering, retrieval, and orchestration 📍Strong backend fundamentals (Python, Postgres, etc.)
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