Software Engineer, Growth Platform

Ramp
New York, NY (HQ)Up to $10kPosted 7 April 2026

Job Description

Software Engineer, Growth Platform ABOUT RAMP Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $100B in annualized spend flows in and out of 50,000+ 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. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. ABOUT THE ROLE Growth engineering builds the systems and applications that power every growth channel at Ramp. As an engineer on this team, you’ll own foundational problems ranging from high volume data ingestion and interfaces to customer-facing applications and AI-powered workflows. You’ll partner closely with product, data, and design, and work directly with stakeholders across growth, sales, and finance. This role offers high ownership, broad technical scope, and the opportunity to directly shape Ramp’s growth engine and scale Ramp to its next millions of users. Check out our Engineering Blog https://builders.ramp.com/ to learn more about our tech stack, mission, and values! WHAT YOU’LL DO - Build software that helps grow Ramp to its next millions of users - Build and scale internal platforms and applications (e.g. workflow orchestration, incentives, sales and marketing apps) that power growth across the company - Design and maintain data ingestion and activation pipelines across Ramp products, internal business systems, external systems, and third-party data - Apply AI/LLMs to unstructured data processing, automation, personalization, and growth signal derivation - Drive business outcomes through experiments and metric-driven software development - Make thoughtful prioritization and scoping decisions around when to build custom solutions vs. leverage third-party tools - Work in a fast-moving, collaborative engineering team alongside partners in product, data, and design WHAT YOU NEED - Minimum of 3 years of experience in a software development role - Experience shipping fast, reliable applications using modern development tools and infrastructure - Comfort operating in a fast-paced, constantly evolving startup environment - Ability to improvise and develop creative solutions when standard approaches fall short; strong bias toward pragmatism in the face of uncertainty - Perpetual curiosity and a passion for continuously improving your craft NICE-TO-HAVES - Startup experience as a technical co-founder or early engineer - Experience with the modern data stack (e.g. ETL tools like Fivetran, workflow orchestrators like Airflow, data platforms like Snowflake) - Experience applying AI/LLMs in production environments - Strong perspective on the engineering development lifecycle (system design, documentation, testing, and long-term codebase health) - Experience building user-facing data or internal business applications - Familiarity with tools that power marketing and sales automation, personalization, and analytics 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 emplo ... (truncated, view full listing at source)
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