Jonathan Tedesco

● Led the transaction risk detection platform supporting Amazon Pay, strengthening fraud prevention and protecting millions of customer payments across the Amazon ecosystem.

● Engineered high-throughput payment risk services in Java, Spring Boot, and Go for real-time transaction analysis and external fraud API integration.

● Constructed streaming and batch data pipelines using Apache Kafka, Spark Streaming, Airflow to process high‑volume transaction and user activity data.

● Designed distributed data storage using DynamoDB and Amazon Aurora to manage transaction risk events and customer activity records.

● Integrated Python, TensorFlow, and Spark-based fraud models into production risk services, improving fraud detection precision and recall by over 20%.

● Created internal investigation dashboards in React, Next.js, and TypeScript to visualize transaction risk scores and support fraud review workflows.

● Provisioned scalable cloud infrastructure using AWS EC2, S3, Lambda, and Docker to support large‑scale payment risk processing services.

● Owned observability and monitoring for transaction risk services, instrumenting systems across Datadog, CloudWatch, Prometheus, and Grafana to detect latency spikes, failures, and reliability issues faster.

● Implemented Git workflows with trunk-based development, GitHub Actions CI/CD, and code review processes, reducing merge conflicts by 50% and speeding up feature delivery across distributed teams.

● Mentored 10+ engineers on microservices architecture, distributed systems design, and scalable payment platform development.

● Leveraged AI-assisted development tools, including Cursor and Claude Code, to reduce boilerplate coding time and speed up debugging and refactoring.

● Architected the SpotMe fee‑free overdraft program, supporting scaled debit card overdraft coverage from early MVP through nationwide rollout.

● Developed the customer dashboard UI using React, Next.js, TypeScript, Material UI, and Tailwind CSS, giving members a clear self-service view of balances, transactions, eligibility, and overdraft coverage.

● Built low-latency backend services in Node.js to process high-volume authorization requests with asynchronous workflows and resilient failure handling.

● Developed real-time overdraft eligibility logic in Ruby on Rails to support transaction validation and customer coverage decisions.

● Created Kafka, Spark Streaming, and Airflow pipelines to process account and transaction events for risk evaluation and operational monitoring.

● Designed PostgreSQL and Redis data stores with indexing and caching strategies to support high‑volume, low‑latency authorization workloads.

● Delivered customer-facing account dashboards in React, Next.js and TypeScript to show balances, recent activity, and overdraft‑style coverage indicators.

● Deployed microservice-style services on Azure using Azure VM, Blob Storage, and Azure SQL Database, along with Docker and CI/CD pipelines, to support high-availability financial systems.

● Shipped SaaS-oriented customer dashboard features for a financial platform, increasing self-service access to account data and overdraft coverage information.