Senior C# Full-Stack Engineer — AI Data & Infrastructure

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 — working on real production systems with genuine, measurable impact.

This is a fully remote contract role with flexible hours. If you're a sharp systems thinker who loves solving hard infrastructure problems, this is the kind of work that will actually push you.

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

• Design, build, and optimize high-performance C# systems supporting large-scale AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for data annotation, validation, and quality control at scale
• Improve reliability, performance, and safety across existing C# codebases — hunt down bottlenecks and ship scalable fixes
• Collaborate directly with data, research, and engineering teams to support model training and evaluation workflows
• Identify edge cases and systemic issues in data and system behavior and implement robust solutions
• Participate in synchronous design reviews to iterate on architecture and implementation decisions

• Full-stack developer with a strong systems programming background and 3–5+ years of professional C# experience
• Confident writing production-quality code with a focus on modern C# standards and best practices
• Deep understanding of performance optimization, concurrency (threading, atomics), and memory safety
• Clear, precise written and verbal communicator — you can articulate technical decisions without hand-waving
• Self-directed and reliable when working remotely with minimal supervision
• Native or fluent English speaker
• Able to commit 20–40 hours per week on a consistent basis

• Prior experience with data annotation, data quality pipelines, or AI evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking infrastructure
• Experience with distributed systems or developer tooling
• Background working in fast-moving research or applied ML environments

• Work directly with leading AI labs on cutting-edge production systems — not toy projects
• Fully remote and flexible — structure your work around your life
• Freelance autonomy with the focus and momentum of high-impact engineering work
• Collaborate with world-class data, research, and engineering teams pushing the frontier of AI
• Potential for ongoing work and contract extension as projects scale