Remote Senior C# Backend Engineer — AI Data Platform

Alignerr Corp.; Seattle (WA); Remote; USD 96,000 - 165,000; Part time

Job summary

Alignerr is seeking a Senior Backend Engineer (C#) to design and build data pipelines, annotation tooling, and evaluation infrastructure powering AI labs. This fully remote, hourly contract role offers 20–40 hours per week and the chance to work on production AI systems.

You will design high-performance C# systems, develop backend services for data annotation and validation, and collaborate with cross-functional teams to ensure scalable, reliable infrastructure for model training and evaluation.

Qualifications

• 5+ years of professional experience building scalable backend services in C#.
• Strong experience with RESTful APIs and RPC services.
• Experience with cloud-native data services and message bus architectures.
• Deep systems programming background.

Responsibilities

• Design, build, and optimize high-performance C# systems supporting AI data pipelines and model evaluation workflows.
• Develop backend services and tooling for large-scale data annotation, validation, and quality control.
• Improve reliability, performance, and safety across existing C# codebases.
• Collaborate with data, research, and engineering teams to support model training and evaluation infrastructure.
• Identify bottlenecks and edge cases in data and system behavior, then implement scalable, production-ready fixes.
• Participate in synchronous design reviews to iterate on architecture and implementation decisions.

Skills

5+ years in C# backend

RESTful APIs

RPC services

Cloud-native data services

Message bus architectures

Systems programming

Job description

Alignerr is seeking a Senior Backend Engineer (C#) to design and build data pipelines, annotation tooling, and evaluation infrastructure powering AI labs. This fully remote, hourly contract role offers 20–40 hours per week and the chance to work on production AI systems.

You will design high-performance C# systems, develop backend services for data annotation and validation, and collaborate with cross-functional teams to ensure scalable, reliable infrastructure for model training and evaluation.