Principal Systems Engineer (C++) - AI Infrastructure
About this role
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 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 contract role working on real production systems — not toy projects. You'll be embedded in high-impact engineering workflows alongside researchers and engineers at the frontier of AI development. - 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 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 memory safety across existing production C++ codebases - Collaborate with data, research, and engineering teams to support model training and evaluation infrastructure - Identify bottlenecks and edge cases in system and data behavior — then implement clean, scalable fixes - Participate in synchronous design reviews to iterate on architecture and implementation decisions Who You Are - Native or fluent English speaker with strong written and verbal communication skills - Full-stack developer with a deep systems programming background and production C++ experience - 5+ years writing production-grade C++ for large-scale, high-performance systems - Advanced knowledge of build system architecture and package management strategies - Experienced in designing reliable systems with rigorous error handling and memory safety practices — including the use of memory sanitizers - Able to commit 20–40 hours per week with professional reliability Nice to Have - Prior experience with data annotation, data quality pipelines, or model evaluation systems - Familiarity with AI/ML workflows, model training, or benchmarking infrastructure - Background in distributed systems design or developer tooling Why Join Us - Work directly on production systems used by leading AI research labs - Fully remote and async-friendly — work from wherever you do your best thinking - Freelance autonomy with the structure and consistency of meaningful long-term projects - Make a tangible impact on the infrastructure that trains and evaluates frontier AI models - Potential for ongoing work and contract extension as new projects launch
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