Remote Backend Engineer — Real-Time Python & FastAPI Scaling

Download Moments; New York (NY); Hybrid; USD 125.000 - 180.000; Vollzeit

Zusammenfassung

Download Moments is seeking a backend engineer to scale our Python/FastAPI services across San Francisco, New York, and remote environments. You will work on a FastAPI backend, async processing pipelines, and real-time notification systems hosted on GCP, with MongoDB as the data store.

Join a fast-paced, small team delivering real-time photo delivery and sharing features. The role focuses on building APIs, optimizing processing pipelines, and ensuring robust observability and data performance at

Qualifikationen

• 3+ years of backend engineering experience.
• Strong Python skills with FastAPI or similar async frameworks.
• Experience with cloud infrastructure (GCP, AWS, or Azure).
• Familiarity with message queues and async task processing.
• Experience with MongoDB or similar NoSQL databases.
• Comfortable working in a fast-paced, small team environment.

Aufgaben

• Build and maintain API endpoints in FastAPI serving the mobile app.
• Design and optimize async processing pipelines for photo delivery.
• Work on real-time notification and photo sharing systems.
• Improve observability, monitoring, and error handling across services.
• Manage data models and queries in MongoDB for performance at scale.
• Collaborate with the iOS team on API contracts and data sync strategies.

Kenntnisse

Python

FastAPI

GCP

Async processing

API design

Observability

Tools

MongoDB

Google Cloud Platform (GCP)

Jobbeschreibung

Download Moments is seeking a backend engineer to scale our Python/FastAPI services across San Francisco, New York, and remote environments. You will work on a FastAPI backend, async processing pipelines, and real-time notification systems hosted on GCP, with MongoDB as the data store.

Join a fast-paced, small team delivering real-time photo delivery and sharing features. The role focuses on building APIs, optimizing processing pipelines, and ensuring robust observability and data performance at