Lead Backend Engineer - AI Tooling

Build production AI infrastructure

Design and improve Python systems that support AI data pipelines, training and evaluation. Work on production code, with emphasis on dependable services, efficient processing and practical research tooling.

• Build backend services and tools for data annotation, validation and quality control at scale.
• Improve reliability, performance and correctness in existing codebases.
• Find system bottlenecks, data edge cases and failure modes, then implement fixes that support growing workloads.
• Coordinate with data, research and engineering groups around model training and evaluation needs.
• Lead live code reviews and contribute to system architecture decisions.
• Design REST/GraphQL APIs and database schemas, including authentication and authorization flows.

Required engineering experience

The role calls for 5+ years of professional production experience in Python. A strong full-stack development background and systems programming foundation are required.

Experience with modern web frameworks and strict type enforcement is required. You should be comfortable leading code reviews and system design discussions.

Native or fluent English is required, with clear written and spoken communication. Consistent availability for 20–40 hours per week is required, along with dependable delivery in a remote engineering environment.

Helpful additional background

Experience with annotation systems, data quality processes or model evaluation is useful. Familiarity with AI/ML workflows, training or benchmarking infrastructure, distributed systems and developer tooling also strengthens a candidacy.

Experience collaborating directly with research or ML engineering groups is valued.

Contract and collaboration

This is a fully remote hourly contract with flexible working arrangements. The commitment is 20–40 hours each week, with technical reviews and cross-functional collaboration forming part of the work.

The arrangement combines freelance independence with production engineering assignments. Continued projects and contract extensions may become available as new research work launches.