Lead Backend Engineer - AI Tooling

Lead Backend Engineer — AI Tooling

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