About Ramp

At Ramp, we’re rethinking how modern finance teams function in the age of AI. We believe AI isn’t just the next big wave. It’s the new foundation for how business gets done. We’re investing in that future — and in the people bold enough to build it.

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 50,000 businesses, from family-owned farms to e-commerce giants to space startups, have saved $10B and 27.5M hours with Ramp. Founded in 2019, Ramp powers the fastest-growing corporate card and bill payment platform in America, and enables over $100 billion in purchases each year.

Ramp’s investors include Lightspeed Venture Partners, Thrive Capital, Sands Capital, General Catalyst, Founders Fund, Khosla Ventures, Sequoia Capital, Greylock, Redpoint, and ICONIQ, 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.

Ramp has been named to Fast Company’s Most Innovative Companies list and LinkedIn’s Top U.S. Startups for more than 3 years, as well as the Forbes Cloud 100, CNBC Disruptor 50, and TIME Magazine’s 100 Most Influential Companies.

About the Role

The Applied AI team at Ramp is at the forefront of leveraging AI to drive innovation across our platform. We are seeking strong full-stack engineers who are proficient in web frameworks, backend development, and infrastructure. You will work on exciting projects such as AI Agents, Retrieval-Augmented Generation, Structured Extraction (we made https://github.com/1rgs/jsonformer), internal tooling for customer-facing teams, fine-tuning models, and build infrastructure for LLM inference. If you're passionate about working on real production use cases of large language models (LLMs) and want to contribute to groundbreaking AI applications, this role is for you.

What You’ll Do

• Ship full-stack AI projects end to end

• Build and integrate components for AI infrastructure, supporting production-level inference and fine-tuning

• Develop and improve engineering processes, tools, and systems to scale AI solutions across Ramp

• Create tools and internal platforms to enhance the productivity and capabilities of Ramp's AI and engineering teams

What You Need

• Proficiency in full-stack development, with a strong understanding of web frameworks, backend systems, and cloud infrastructure

• A track record of working on full-stack AI projects, particularly those involving production use cases of LLMs

• Experience building backend systems and infrastructure that can support AI-driven products

Benefits (for U.S.-based full-time employees)

• 100% medical, dental & vision insurance coverage for you

  • Partially covered for your dependents

  • One Medical annual membership

• 401k (including employer match on contributions made while employed by Ramp)

• Flexible PTO

• Fertility HRA (up to $10,000 per year)

• Parental Leave

• Unlimited AI token usage

• Pet insurance

• Centralized home-office equipment ordering for all employees

• Health and Wellness stipend

• In-office perks: lunch, snacks, drinks, and more

• Budget for intra-office travel

• Relocation support to NYC or SF (as needed)

Referral Instructions

If you are being referred for the role, please contact that person to apply on your behalf.

Other notices

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Beware of recruiting scams: Ramp will only contact you through official @Ramp.com email addresses and will never ask for payment or sensitive personal information during the hiring process.

Ramp Applicant Privacy Notice