Senior Backend Engineer - AI Data Pipelines & Annotation

Alignerr; New York (NY); On-site; USD 83,000 - 124,000; Full time

Job summary

Alignerr is seeking a Senior Python Full-Stack Engineer for data annotation systems and AI training infrastructure. This fully remote, hourly contract role focuses on building high-performance Python pipelines, annotation tooling, and evaluation systems used by leading AI labs to train models.

You will design scalable backend services, manage asynchronous tasks, optimize databases, and collaborate with data and research teams to enable end-to-end model training workflows.

Qualifications

• 3–5+ years of professional Python experience.
• Experience with asynchronous task queues and background job processing.
• Strong systems programming background with high-throughput data handling.

Responsibilities

• Design, build, and optimize high-performance Python systems powering AI data pipelines and model evaluation workflows.
• Develop full-stack backend services and tooling for large-scale data annotation, validation and quality control.
• Build and maintain asynchronous task queues for long-running background jobs at scale.
• Optimize database queries for high-read/write workloads and serve data via real-time protocols such as WebSockets.
• Improve reliability, performance, and safety across existing Python codebases.
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows.
• Identify bottlenecks and edge cases, implementing scalable production-ready fixes.
• Participate in synchronous design reviews to iterate on architecture and implementation decisions.

Skills

Python

Full-stack development

Async processing

WebSockets

Tools

PostgreSQL

Redis

Docker

Job description

Alignerr is seeking a Senior Python Full-Stack Engineer for data annotation systems and AI training infrastructure. This fully remote, hourly contract role focuses on building high-performance Python pipelines, annotation tooling, and evaluation systems used by leading AI labs to train models.

You will design scalable backend services, manage asynchronous tasks, optimize databases, and collaborate with data and research teams to enable end-to-end model training workflows.