Python Software Engineer - AI Workflows

About The Role

What if your Python expertise could directly shape the infrastructure powering the next generation of AI? We're looking for senior Python engineers to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on — production-grade work that makes a real difference in how AI models are trained and improved.

This is a fully remote contract role with flexible hours. If you're a strong Python engineer who wants to work on genuinely interesting infrastructure problems at the frontier of AI development, this is built for you.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 20–40 hours/week

• Design, build, and optimize high-performance Python systems supporting AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
• Identify and resolve bottlenecks, edge cases, and reliability issues across existing codebases
• Improve performance, safety, and maintainability across Python infrastructure used in real AI production environments
• Collaborate with data, research, and engineering teams to support model training and evaluation workflows
• Participate in synchronous design reviews and iterate on system architecture and implementation decisions

• Native or fluent English speaker with clear written and verbal communication
• Full-stack developer with a strong systems programming background
• 3–5+ years of professional experience writing production-grade Python
• Disciplined about code quality — you naturally reach for linters, formatters, and comprehensive test coverage
• Experienced integrating AI services and third-party APIs, with solid instincts for error handling and edge case management
• Able to commit 20–40 hours per week with reliability and consistency

• Prior experience with data annotation, data quality, or evaluation systems
• Familiarity with AI/ML workflows, model training, or benchmarking pipelines
• Experience with distributed systems or developer tooling
• Background working directly with AI research teams or labs

• Work on real production systems powering cutting-edge AI at leading research labs
• Fully remote and flexible — structure your week the way that works for you
• Meaningful, high-impact engineering work — not maintenance tickets, but systems that matter
• Freelance autonomy with the substance and scope of serious engineering work
• Potential for ongoing work and contract extension as new projects launch