C# Infrastructure Engineer - Data Pipelines

C# Infrastructure Engineer — Data Pipelines (AI Training)

About The Role

What if your expertise in C# and systems engineering could directly shape the infrastructure powering the next generation of AI? We're looking for a Senior C# Full-Stack Engineer to design and build the high-performance data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and improve their models.

This is a fully remote contract role working on real production systems at the cutting edge of AI research. If you thrive on solving hard infrastructure problems and want your work to have genuine, measurable impact — this is the role for you.

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

• Native or fluent English speaker with clear written and verbal communication skills
• Full-stack developer with a strong systems programming background
• 5+ years of professional experience writing production-grade C#
• Deep experience building streaming data pipelines using asynchronous streams and reactive programming concepts
• Proven ability to optimize I/O-bound operations and implement resilient retry policies for distributed data ingestion
• Self-directed and reliable — you can own complex work across a 20–40 hour weekly commitment
  
  

• Prior experience with data annotation, data quality, or model evaluation systems
• Familiarity with AI/ML workflows, model training pipelines, or benchmarking infrastructure
• Experience with distributed systems or developer tooling at scale
  
  

• Work directly with leading AI research labs on real, high-impact production systems
• Fully remote and asynchronous-friendly — work from wherever you do your best thinking
• Freelance autonomy with the substance and structure of meaningful, senior-level engineering work
• Contribute to infrastructure that shapes how next-generation AI models are built and evaluated
• Potential for ongoing work and expanded scope as projects grow