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Company practice
Ramp mock interviews
Выберите роль в Ramp, ответьте вслух на вопросы AI-интервьюера и получите вердикт по компетенциям после интервью.
4 ролиPostgreSQLPythonAirflowAWS
Создать свое интервьюРоли для тренировки
Ramp
ML / AI
Applied AI Engineer
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.
PythonLLMsRAGRamp
infrastructure
Senior Software Engineer, 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.
AWSKubernetesTerraformRamp
backend
Software Engineer, Backend (Senior & Staff)
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.
PythonFlaskPostgreSQLRamp
data
Software Engineer, Data Platform
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.
PythonSparkAirflow
ExoForm не аффилирован с Ramp. Это независимая тренировочная страница.
FAQ
Можно ли пройти интервью голосом?
Да. ExoForm проводит живое голосовое интервью, задает уточнения и после завершения показывает оценку и разбор ответов.
Нужно ли платить сразу?
Нет. Можно начать бесплатно, а позже перейти на платный план, если нужно больше тренировок.