About the role
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.
About
the Role As a software engineer on the AI Soltuions team, you will co-lead customer engagements with an AI Solutions Strategist . The Strategist owns business discovery, ROI narrative, stakeholder alignment, and rollout planning. The engineer owns technical discovery, solution design, prototyping, implementation, and production readiness. This is a deeply client-facing role. You will spend significant time with customers and end users, moving projects from bootcamp and workflow discovery through implementation, launch, and steady production usage. What You’ll Do Translate customer goals into clear system
requirements and non-functional
requirements covering security, privacy, reliability, performance, scalability, and cost. Partner directly with customers to understand current workflows, constraints, systems, data quality, and adoption blockers. Create and maintain solution architecture artifacts: System context and data flow diagrams Integration plan across Ramp and customer systems Security model covering permissions, access patterns, and auditability Evaluation plan covering quality metrics, acceptance tests, and red-teaming Operational plan covering monitoring, alerting, incident response, and runbooks Leverage core Ramp primitives to build efficiently, reusing existing product capabilities wherever possible. Prototype and validate workflows with end users to de-risk the approach and prove product-market fit. Drive projects from bootcamp and technical discovery through implementation, production launch, and operational handoff. Ensure deployed workflows are reliable, supportable, measurable, and adopted by customer teams. Convert deployments into reusable patterns, components, and playbooks for future AI Solutions projects. What You Need Experience shipping production software in high-ownership environments. Ability to work directly with enterprise customers from discovery through production implementation. Experience in solutions architecture, technical consulting, forward deployed engineering, or pre-sales engineering. Strong fundamentals in ML/GenAI, including problem decomposition, evaluation, and deployment trade-offs. Strong coding ability in at least one of: Python, TypeScript/JavaScript, Java, Go, or similar. Ability to design secure, scalable systems and produce clear technical documentation. Comfort working across APIs, integrations, data pipelines, customer systems, and cloud infrastructure. Experience with cloud architecture on AWS, GCP, or Azure, and distributed systems patterns. Experience building LLM systems, including RAG, agents, monitoring, and evals. Willingness to travel up to ~75% as needed, flexible based on project needs and client needs