Backend Engineer (Rust/Python) — High-Scale AI & Ops

MoneyLion; Jackson (MS); On-site; USD 110,000 - 160,000; Full time

Job summary

MoneyLion is building a small, highly technical backend team responsible for critical production services that handle high traffic. Our stack includes Rust and Python, deployed to Kubernetes clusters on Google Cloud Platform.

You’ll design, implement, and monitor scalable services while participating in on-call rotation and applying AI tooling to improve reliability and performance. You will collaborate with peers to continuously improve code, infrastructure, and processes, delivering robust

Qualifications

• Backend development experience with Rust and/or Python.
• Experience running production systems.
• Familiarity with Kubernetes and cloud environments (ideally GCP).
• Willingness to participate in on-call duties.
• Interest in adopting and experimenting with AI tooling.
• Attention to reliability, scalability, and operational excellence.

Responsibilities

• Design, implement, and maintain robust backend services in Rust and Python
• Operate and monitor production systems at large scale
• Troubleshoot incidents, optimize performance, and ensure high availability
• Participate in on-call rotation to keep services reliable 24/7
• Use state-of-the-art AI tools to enhance development, monitoring, and operational efficiency
• Collaborate with engineers to improve code, infrastructure, and processes

Skills

Rust

Python

Backend development

On-call experience

Kubernetes

Cloud environments

AI tooling

Tools

Google Cloud Platform

Kubernetes

Job description

MoneyLion is building a small, highly technical backend team responsible for critical production services that handle high traffic. Our stack includes Rust and Python, deployed to Kubernetes clusters on Google Cloud Platform.

You’ll design, implement, and monitor scalable services while participating in on-call rotation and applying AI tooling to improve reliability and performance. You will collaborate with peers to continuously improve code, infrastructure, and processes, delivering robust