Software Engineer; C Internal Tooling

Software Engineer (C#) — Internal Tooling (AI Infrastructure)

About the role:

What if your C# expertise could directly shape the infrastructure powering the next generation of AI? We’re looking for experienced full‑stack C# engineers to build and improve the systems that leading AI labs depend on — from data annotation pipelines to evaluation harnesses and quality control tooling. This is a fully remote contract role with flexible commitment. You’ll work on real production systems alongside data, research, and engineering teams at the frontier of AI development.

• Organization:
  Alignerr
• Type:
  Hourly Contract
• Location:
  
  Remote
• Commitment: 20–40 hours/week

• Design, build, and optimize high-performance C# systems supporting 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 existing C# codebases
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows
• Identify and resolve bottlenecks and edge cases in data and system behavior with scalable solutions
• Participate in synchronous design reviews to iterate on architecture and implementation decisions
• Build and maintain robust benchmarking and performance evaluation harnesses

• 3–5+ years of professional experience writing production‑grade C#
• Strong full‑stack developer background with solid systems programming fundamentals
• Expertise in interoperability scenarios — such as invoking Python ML models from .NET or wrapping native libraries
• Experienced designing robust harnesses for benchmarking and evaluating system performance
• Native or fluent English speaker with clear written and verbal communication skills
• Able to commit 20–40 hours per week with reliability and consistency

• Prior experience with data annotation, data quality, or evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking pipelines
• Experience with distributed systems or developer tooling
• Background working with or alongside research teams in a fast‑moving environment

• Work on cutting‑edge AI projects alongside leading research labs
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the structure of meaningful, high‑impact technical work
• Build systems that directly influence how next‑generation AI models are trained and evaluated
• Potential for ongoing work and contract extension as new projects launch