Software Engineer, Backend, Marketing Product

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. - Excellent cross-functional communication and a bias toward rapidly shipping measurable user and business outcomes. Nice to Haves - Experience building incentive, rewards, promotion, loyalty, payments, ledger, or financial-authorization systems. - Experience building workflow engines, automation platforms, agent systems, or orchestration infrastructure. - Experience with lifecycle marketing, product growth, paid media, experimentation, CRM, or other marketing technology. - Experience designing human-in-the-loop AI systems, including approvals, evaluations, tool execution, and recovery. - Experience with customer-data pl

4+ years of product engineering experience, ideally at a high-growth tech company, with meaningful time on user-facing or platform-tooling work. Demonstrated track record of building internal tools or platforms that materially reduced repetitive workflows for non-engineers. Strong product instincts and ability to say no, scope down, and ship the right 70% over the wrong 100%. Comfortable with AI/LLM-augmented engineering and have built or shipped agentic workflows, MCP servers, or LLM-powered tooling, or have a strong, opinionated POV on how to. Velocity and ownership; ships without supervision and operates well where the operating model is still being written. Cross-functional empathy to work with marketers and non-engineers.

Own the end-to-end development of self-serve tooling that converts repeated marketing asks into reusable platform capabilities. Examples include an MCP integrated with design system and Prototyper app enabling marketers to go from idea to production-ready landing page in minutes, AI content writing workflows, self-improving experimentation tooling, and programmatic sales asset creation. Be opinionated about agentic and AI-augmented workflows and drive direction of the agent layer. Partner with marketers, designers, and PMs to identify the highest-leverage workflows to automate; role is part platform engineer, part product engineer with user research and collaboration with non-engineers. Set the bar for velocity and quality on a small team with high-stakes. Reduce ticket burden by enabling marketing work to ship without manual intervention.