Are these based on real engineering roles?
Yes. The catalog is built around real engineering role patterns so the practice round feels closer to a live interview.
Company practice
Pick a role, answer follow-up questions out loud, and get a scored verdict after the interview.
Ramp
ML / AI
Embeds LLM-driven intelligence directly into Ramp's finance workflows — categorizing spend, extracting data from receipts and invoices, and automating bookkeeping inside the flow of every dollar a business spends. Builds and evaluates production AI features, prompts, and retrieval pipelines against real transaction data. A technical interview would probe practical LLM application design (retrieval, evaluation, guardrails), how you measure and improve accuracy on noisy financial documents, and integrating model outputs reliably into transactional product flows.
Ramp
Infrastructure
Builds and operates the cloud platform underpinning Ramp's products, owning compute, deployment, observability, and reliability across AWS so product teams can ship safely at fintech scale. Improves CI/CD, infrastructure-as-code, and the resilience of services handling real-time money movement. A technical interview would probe cloud architecture and reliability (scaling, failure domains, observability), infrastructure-as-code design, and how you would diagnose and remediate a production reliability incident.
Ramp
Backend
Builds the core backend systems that authorize payments, categorize spend, flag risk, and close the books for 50,000+ companies moving over $100B in annualized spend through Ramp. Owns services and data models in a Python/Flask and PostgreSQL stack with asynchronous processing over RabbitMQ. A technical interview would probe backend and data-model design for a financial platform, transactional correctness and idempotency, and how you scale and debug high-throughput payment and ledger services.
Ramp
Data
Builds the data platform and pipelines that power Ramp's spend intelligence, analytics, and ML features, ingesting and transforming high-volume transaction data into reliable, queryable datasets. Owns batch and streaming infrastructure and the tooling other engineers use to build on top of data. A technical interview would probe data-pipeline and warehouse design, correctness and idempotency in ETL at scale, and tradeoffs between batch and streaming for financial data.
ExoForm is not affiliated with Ramp. This is an independent practice page.
Yes. The catalog is built around real engineering role patterns so the practice round feels closer to a live interview.
Yes. ExoForm runs a live voice interview, asks follow-ups, and produces structured feedback after the session.
Yes. You can start with the free interview allowance before upgrading for more practice.