C# Infrastructure Engineer - Data Pipelines

About The Role

What if your C# engineering skills could directly shape the infrastructure powering the world's most advanced AI systems? We're looking for a senior C# engineer to design and build the high-performance data pipelines, annotation tooling, and evaluation infrastructure that leading AI labs depend on to train and improve next-generation models.

This is a fully remote, flexible contract role for an experienced engineer who wants meaningful, high-impact work — without the overhead of a full-time commitment.

• 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 safety across existing 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 workflows
• Participate in synchronous design reviews to iterate on architecture and implementation decisions

• Native or fluent English speaker with clear written and verbal communication
• 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
• Skilled at optimizing I/O-bound operations and implementing resilient retry policies for distributed data ingestion
• Able to commit 20–40 hours per week with reliable availability

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

• Work directly on production systems used by leading AI research labs
• Fully remote and flexible — structure your hours around your life
• Freelance autonomy with the depth and consistency of real, ongoing engineering work
• Make a tangible impact on the infrastructure shaping the future of AI
• Potential for ongoing work and contract extension as projects scale