Software Engineer, Backend, Growth

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 $200B in annualized spend flows in and out of 70,000+ 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.

Ramp is building an AI-native platform that changes how Go-to-Market and Product Growth teams create, launch, and improve customer-facing experiences. We are looking for a product-minded backend engineer to help build the infrastructure and services that power modern growth and marketing at Ramp.

The next chapter for this team is to build marketing-led products : intelligent tools that turn strategy into execution, automate complex workflows, and help teams operate across channels with dramatically more leverage.

The team will build across creative production, lifecycle marketing, paid media, account-based marketing, experimentation, incentives, and cross-channel orchestration. Examples include AI-powered systems that produce on-brand campaign assets, automate complex marketing workflows, coordinate audiences and execution, and deliver personalized experiences across email, sales outreach, external channels, and Ramp’s product.

A core part of this mandate is Ramp’s incentives platform. We are building shared infrastructure to safely target, authorize, distribute, redeem, and measure incentives across channels and mediums—including in-app experiences tied to product adoption and growth goals. This requires combining marketer-friendly workflows with governed policies, budget controls, reliable financial operations, and closed-loop measurement.

You will work at the intersection of product engineering, AI, data, marketing, and financial infrastructure. The ideal candidate is a product-minded backend engineer who can translate ambiguous workflows into durable systems. You will build the data models, APIs, integrations, and orchestration capabilities that allow marketers, product teams, and AI agents to safely execute complex work end to end.

What You’ll Do

Build the backend systems that power AI-native marketing and growth products across creative production, experimentation, incentives, and cross-channel orchestration.

Build shared incentives infrastructure for eligibility, targeting, policies, budgets, authorization, issuance, redemption, and outcome tracking.

Enable personalized content and offers across email, sales workflows, external channels, and in-product experiences using shared customer and campaign context.

Design reliable orchestration for long-running work, approvals, scheduling, retries, human intervention, and safe AI or financial execution.

Connect marketing actions and incentive spend to measurable activation, conversion, retention, and revenue outcomes.

Partner across Marketing, Product Growth, Product, Data Science, Finance, and GTM Platform to own systems from early discovery through production adoption and iteration.

What You Need

5+ years of software engineering experience building production backend systems, with strong proficiency in Python or another modern server-side language.

A track record of owning production services, APIs, data models, and distributed or event-driven workflows.

Strong product judgment and system-design fundamentals, including data modeling, asynchronous processing, reliability, testing, and observability.

Experience building governed systems involving permissions, policies, budgets, balances, entitlements, or financial actions.

Experience applying AI to real product workflows—or strong interest in doing so—with an understanding of where deterministic controls and human approval are required.