C# Infrastructure Engineer - Data Pipelines

C# Infrastructure Engineer — Data Pipelines (AI Training) About The Role

What if your deep C# expertise could directly shape the infrastructure powering the world's most advanced AI systems? 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 next-generation models.

What if your deep C# expertise could directly shape the infrastructure powering the world's most advanced AI systems? 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 next-generation models.

This is a fully remote, flexible contract role for experienced engineers who want meaningful, high-impact work — without the constraints of a full-time position.

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

• Design, build, and optimize high-performance C# systems that power 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 — then implement scalable, resilient 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

• 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#
• Proven track record building streaming data pipelines using asynchronous streams and reactive programming patterns
• Experienced optimizing I/O‑bound operations and implementing resilient retry policies for distributed data ingestion
• Able to commit 20–40 hours per week with reliability and consistency

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

• Work on cutting‑edge AI projects alongside leading research labs doing work that actually matters
• Fully remote and flexible — work when and where it suits you
• Freelance autonomy with the structure of meaningful, ongoing technical work
• Make a direct, tangible impact on the infrastructure shaping the future of AI
• Potential for ongoing work and contract extension as new projects launch