Backend Developer - AI Data Services

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

What if your C# expertise could directly shape the infrastructure powering the next generation of AI? We're looking for a Senior C# Full-Stack Engineer to build and optimize the 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 with real technical depth — you'll work on production systems that matter, 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 bottlenecks and edge cases in data and system behavior, and implement scalable fixes
• 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#
• Strong skills in data modeling and database access using ORM frameworks or micro-ORMs for high-performance SQL interactions
• Experienced building secure, well-documented endpoints for data access and manipulation
• 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

• Work directly with leading AI labs on real production infrastructure — not toy projects
• Fully remote and async-friendly — work from wherever you do your best thinking
• Freelance autonomy with the structure of meaningful, ongoing technical work
• Contribute to systems that have a measurable impact on how next-generation AI is built and evaluated
• Potential for extended engagement as new projects and infrastructure needs grow