Lead Backend Engineer - AI Tooling
About this role
About the Role What if your Python expertise could directly shape the infrastructure powering the next generation of AI? We're looking for a Senior Python Full-Stack Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on to train and benchmark their most advanced models. This is a fully remote contract role working on real production systems alongside world-class research and engineering teams. If you thrive at the intersection of backend engineering and cutting-edge AI, this is the opportunity to make a tangible impact at scale. - Organization: Alignerr - Type: Hourly Contract - Location: Remote - Commitment: 20–40 hours/week What You'll Do - Design, build, and optimize high-performance Python 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 - Architect robust REST and GraphQL APIs, design database schemas, and implement authentication and authorization flows - Improve reliability, performance, and safety across existing production Python codebases - Identify bottlenecks and edge cases in data and system behavior, then implement scalable, maintainable fixes - Collaborate closely with data, research, and engineering teams to support model training and evaluation workflows - Lead synchronous code reviews and system design sessions, driving technical decisions with clarity and conviction Who You Are - Native or fluent English speaker with clear written and verbal communication skills - Full-stack developer with a strong systems programming background and 5+ years of professional experience writing production Python backend services - Mastery of modern web frameworks and strict type enforcement patterns in Python - Proven experience architecting APIs, designing database schemas, and implementing auth flows at production scale - A sharp problem-solver who can spot systemic issues and drive meaningful improvements across complex codebases - Able to commit 20–40 hours per week with consistency and reliability Nice to Have - Prior experience with data annotation platforms, data quality systems, or evaluation infrastructure - Familiarity with AI/ML workflows, model training pipelines, or benchmarking systems - Experience with distributed systems, developer tooling, or infrastructure engineering Why Join Us - Work on high-impact, production-grade systems used by leading AI research labs - Fully remote and async-friendly — work from wherever you do your best work - Engage with meaningful engineering challenges at the frontier of AI development - Collaborate with top-tier researchers and engineers on problems that matter - Potential for ongoing work and contract extension as projects evolve and scale
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