Copy of AI Code Reviewer & Systems ...

Join a pioneering initiative focused on elevating advanced AI systems through human feedback. We are seeking experienced software engineers to contribute to the development of large language models (LLMs) by enhancing their understanding of software development practices, debugging, and code quality. This role is central to shaping how AI models evaluate, review, and optimize code in real-world applications.

This opportunity is ideal for engineers passionate about systems analysis, code quality improvement, and tackling complex technical challenges. You will play a crucial role in AI training projects by evaluating model outputs, refining logic, and identifying potential system vulnerabilities.

What You'll Do:

• Develop objective, verifiable evaluation criteria (rubrics) for system performance.
• Review system logs and execution paths to enhance reliability and code quality.
• Refactor code and optimize system behavior for optimal outcomes.
• Test systems for vulnerabilities, including data exposure and edge-case failures.
• Provide detailed, high-quality feedback on system performance and outputs.

Qualifications:

Requirements:

• 2+ years of experience in backend engineering, AI automation, or systems integration.
• Strong proficiency in at least two programming languages (e.g., Python, JavaScript, Go, Java).
• Experience working with SQL databases.
• Proven ability to build and maintain production-grade systems.
• Experience working in live (non-mocked) environments with multi-step interactions.
• Strong analytical skills and attention to detail.

Nice to Haves:

• Experience with multi-stage system workflows and coordination tasks.
• Familiarity with integrating tools such as APIs, databases, or external platforms.
• Understanding of system vulnerabilities (e.g., privacy leaks, prompt injection, access escalation).
• Experience working with AI systems or agent-based workflows.
• Comfort working with persistent state tracking or similar frameworks.

Additional Information:

• Fully remote and flexible work schedule.
• Project-based engagement with no guaranteed hours.
• Work on tasks based on availability and project assignment.
• Payment is based on completed tasks only.
• Must accept project invitations before beginning work.
• Freelancers may accept or decline tasks depending on availability.
• No guaranteed workload; volume may vary weekly.