Backend Software Engineer · New York, NY
I build APIs that keep data consistent at scale.
I'm a backend engineer working mostly in Python and TypeScript. At BentoBox I built payment
and point-of-sale integrations for more than 5,000 restaurants, and at American Express I
moved customer acquisition APIs from REST to GraphQL. Lately I've been building
event-driven systems on AWS and contributing to
Replay Manager for Slippi,
an open-source tournament tool.
- Data updates synced monthly
- 10M+
- Restaurants served
- 5,000+
- Customer accounts on a unified schema
- 20M+
- Lower API latency
- 40%
Experience
Jun 2022 – Feb 2023
Software Engineer, Backend BentoBox
- Built a Django API for Fiserv gift card purchases and redemptions, supporting over 50,000 transactions per month across all BentoBox locations.
- Engineered a synchronization engine that processed over 10 million data updates monthly across five POS systems, ensuring sub-second data consistency for 5,000+ restaurants.
- Implemented a catering integration with Clover POS, enabling seamless ordering and supporting over 10,000 monthly transactions.
- Designed microservices tailored to each POS system, ensuring a consistent user experience for over 5,000 restaurants.
May 2021 – May 2022
Software Engineer, Backend American Express
- Optimized customer acquisition APIs by implementing GraphQL persisted queries and server-side caching in JavaScript, reducing data retrieval latency by 40% for millions of monthly interactions.
- Designed a unified data schema for over 20 million customer accounts and led the migration of backend APIs onto it, replacing the legacy REST endpoints.
Jun 2020 – Aug 2020
Software Engineer Intern, Backend American Express
- Built a backend tool that automatically generates API schemas from existing REST endpoints.
- Modernized APIs by architecting and deploying components that integrate with a modern query language system.
Projects
2026 · Personal project
PythonRaspberry PiIoT CoreLambdaDynamoDBS3
- Built a Raspberry Pi plant monitor in Python logging hourly climate data and daily photos.
- Streamed sensor data to AWS IoT Core over MQTT using X.509 certificate authentication, and routed it through an IoT Rule into DynamoDB, with keys designed for time-range queries.
- Moved Gemini image analysis to an event-driven AWS Lambda triggered by S3 photo uploads. It queries 24 hours of readings from DynamoDB, loads secrets from SSM Parameter Store, and retries when the API is rate-limited.
Hourly
- DHT11 sensor
- Raspberry Pi
- IoT Core (MQTT)
- IoT Rule
- DynamoDB
Daily
- Webcam photo
- S3
- Lambda
- Gemini analysis
- Discord report
- Contributed start.gg GraphQL mutations to an open-source tournament tool, automating set calling and set progress tracking for organizers.
- The tool is used at events with 1,000+ entrants and up to 100,000 concurrent stream viewers.
More on GitHub
All repositories on GitHub
Skills
- Languages
- PythonJavaScript / TypeScriptJavaSQLCC++C#
- Backend
- DjangoGraphQLRESTNodeExpressReact
- Cloud & ops
- AWS LambdaS3DynamoDBIoT CoreIAMKubernetesDatadog
- AI
- GenAIClaude
Education
B.S. Software Engineering, Arizona State University, Mesa, AZ · May 2021