Principal Systems Engineer (C++) - AI Infrastructure
Company: Alignerr
Location: New York, NY (Remote)
Type: Full-time
Remote: Yes
Posted: 2026-08-17
About this role
Principal Systems Engineer (C++) — AI Infrastructure
About The Role
What if your systems engineering expertise could directly shape the infrastructure powering the world's most advanced AI models? We're looking for a Principal C++ Systems Engineer to design and build high-performance data pipelines, annotation tooling, and evaluation infrastructure used by leading AI research labs.
This is a fully remote, flexible contract role for an experienced engineer who thrives on solving hard problems at scale — someone who cares deeply about performance, reliability, and clean systems design.
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 20–40 hours/week
What You'll Do
- 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 memory safety across production C++ codebases
- Collaborate closely with data, research, and engineering teams to support model training and evaluation workflows
- Identify bottlenecks and edge cases in system behavior, then implement scalable, maintainable solutions
- Participate in synchronous design reviews to iterate on architecture and implementation decisions
Who You Are
- 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++ for large-scale systems
- Advanced knowledge of build system architecture and package management strategies
- Experienced designing reliable systems with rigorous error handling and memory sanitizers
- Self-directed and capable of committing 20–40 hours per week in a remote contract environment
Nice to Have
- Prior experience with data annotation, data quality pipelines, or evaluation system...