Software Developer | $40-$90/hr Remote
Overview
This role involves building and maintaining scalable back-end and full-stack applications to help train next-generation AI systems. The work directly shapes how AI models learn and reason by providing high-quality, real-world input. No prior AI experience is required—domain expertise in software development is what matters. The position is part-time and remote, requiring collaboration across distributed teams.
What You'll Do6
- 1Design, implement, and maintain scalable back-end and full-stack applications
- 2Collaborate with cross-functional team members to deliver high-quality software solutions
- 3Write clean, efficient, and well-documented code following best engineering practices
- 4Troubleshoot, debug, and optimize existing codebases to improve performance and reliability
- 5Participate in code reviews, technical discussions, and architectural planning
- 6Contribute to the full software development lifecycle from concept to deployment
Requirements6
- 13+ years of hands-on experience in software development (backend, frontend, or full-stack)
- 2Proficiency in building scalable, reliable, and maintainable software systems
- 3Experience working in remote, collaborative, and agile environments
- 4Expertise in modern development tools, version control systems, and CI/CD pipelines
- 5Strong problem-solving skills with keen attention to detail
- 6Excellent written and verbal communication skills with a high standard for clarity and professionalism
Who Should Apply
Experienced software developers with at least 3 years of hands-on work in backend, frontend, or full-stack roles who thrive in remote, agile settings. The ideal candidate is self-driven, communicates clearly, and is comfortable building scalable systems—even if they have no prior AI experience. Domain knowledge and a passion for quality code are most important.
Salary Insight
Pay range is $40-$90 per hour, reflecting part-time remote work.
Required Skills
Application Tip
Highlight your experience building scalable, production-grade systems and mention any familiarity with cloud platforms like AWS, GCP, or Azure—even if you haven't worked directly on AI projects.