AI Code Reviewer & Systems Evaluation Engineer 2
Company Description
An enterprise client is currently seeking experienced software engineers to contribute to improving advanced AI systems through human feedback. This work supports leading AI organizations in training large language models to better understand software development practices, debugging, and code quality. This is part of a cutting-edge initiative focused on enhancing how AI systems write, review, and optimize code in real-world scenarios. You’ll play a key role in shaping how AI models evaluate performance, detect issues, and generate reliable outputs.
Job Description
This opportunity is ideal for engineers who enjoy analyzing systems, improving code quality, and working on complex technical challenges. You will contribute to AI training projects by evaluating outputs, refining logic, and identifying potential vulnerabilities. What You'll Do: Develop objective, verifiable evaluation criteria (rubrics) for system performance Review system logs and execution paths to improve reliability and code quality Refactor code and optimize system behavior toward ideal 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