Search
Go
This job is no longer accepting applications
This listing was closed on Jul 20, 2026.
Browse Open JobsBack End Developer (AI Infrastructure)
Summary by AIEngineer.careers
Back End Developer (AI Infrastructure) is a AI Infrastructure Engineer role (contract). with Alignerr. in REMOTE, WORLDWIDE. Compensation shown: $80K–$120K. Imported listing (source: usaremotejobs.app). Apply on the employer's site (usaremotejobs.app).
Imported listing (source: usaremotejobs.app) · Apply on usaremotejobs.app
REMOTE · WORLDWIDE
$80K–$120K
Contract
SENIOR
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from usaremotejobs.app
Join Alignerr as a Back End Developer to design and optimize server-side systems and APIs powering AI products. This is a fully remote, flexible contract role (10-40 hours/week) where you'll build scalable infrastructure for AI training and inference.
Responsibilities
- Design, develop, and maintain robust back end services, APIs, and data pipelines
- Build scalable, high-performance server-side architecture to support AI training and inference workloads
- Write clean, well-documented, and testable code following engineering best practices
- Integrate with databases, message queues, cloud services, and third-party APIs
- Optimize system performance, reliability, and scalability as usage grows
- Collaborate asynchronously with distributed teams of engineers, researchers, and product leads
- Troubleshoot production issues, conduct code reviews, and contribute to architectural decisions
- Work independently on task-based and project-based assignments on your own schedule
Requirements
- Proficient in one or more back end languages — Python, Go, Java, Node.js, Rust, or similar
- Solid understanding of RESTful API design, microservices architecture, and distributed systems
Alignerr
San Francisco · US · 2380+ employees
Alignerr is a professional development and AI training services company that connects experts with opportunities to train and align large language models. It employs a large, remote, and distributed network of professionals to improve AI safety and performance.
