Remote C# Infrastructure Engineer — AI Data Pipelines

Alignerr

United States

Remote

MXN 1,409,000 - 2,817,000

Part time

9 days ago

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Benefits offered by this job

Fully remote
Flexible hours
Contract extension potential

Job summary

Alignerr is seeking a Senior C# Infrastructure Engineer to design high-performance data pipelines powering AI training and evaluation. This fully remote role emphasizes building streaming data solutions and robust tooling for large-scale annotation and validation workflows.

You will collaborate with data, research, and engineering teams to optimize distributed systems, improve reliability, and shape the infrastructure used by leading AI labs.

Qualifications

  • 5+ years of professional experience writing production-grade C#
  • Experience building streaming data pipelines using asynchronous streams and reactive programming patterns
  • Commit to 20–40 hours per week and maintain reliability

Responsibilities

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

Skills

C#
Full-stack
Reactive streams
I/O optimization

Job description

Alignerr is seeking a Senior C# Infrastructure Engineer to design high-performance data pipelines powering AI training and evaluation. This fully remote role emphasizes building streaming data solutions and robust tooling for large-scale annotation and validation workflows.

You will collaborate with data, research, and engineering teams to optimize distributed systems, improve reliability, and shape the infrastructure used by leading AI labs.

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