Senior Backend Engineer; C AI Data Platform

What if your C# expertise could directly shape the infrastructure powering the next generation of AI? We're looking for a Senior Backend 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 with meaningful technical scope. You'll work on real production systems — not toy projects — 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 backend systems in C# supporting AI data pipelines and evaluation workflows
• Develop backend services and tooling for large-scale data annotation, validation, and quality control
• Build and maintain RESTful APIs and RPC services for reliable inter-service communication
• Integrate with cloud-native data services and orchestrate workflows via message bus architectures
• Improve reliability, performance, and safety across existing C# codebases
• Identify bottlenecks and edge cases in data and system behavior, then implement scalable, durable fixes
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows
• Participate in synchronous design reviews to iterate on architecture and implementation decisions

• 5+ years of professional experience building scalable backend services in C#
• Strong systems programming background with full-stack exposure
• Mastery of modern frameworks for building RESTful APIs and RPC services
• Experienced with cloud-native data services and message bus / event-driven architectures
• Native or fluent English speaker with clear written and verbal communication skills
• Self-directed and reliable — able to commit 20–40 hours per week and deliver consistently
• Sharp eye for performance bottlenecks, edge cases, and system-level failure modes

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

• Work on cutting-edge AI infrastructure projects alongside leading research labs
• Fully remote and flexible — work from anywhere, on a schedule that suits you
• Freelance autonomy with the structure and purpose of high-impact engineering work
• Make a direct, tangible contribution to the systems that shape how AI models are built and evaluated
• Potential for ongoing work and contract extension as new projects launch