Note: The job is a remote job and is open to candidates in USA. 24-MAG LLC is offering a remote consulting opportunity for experienced backend engineers with a focus on backend code evaluation and assessment. The role involves using modern coding agents to evaluate and review complex backend engineering tasks, ensuring the quality and performance of backend implementations.

Responsibilities

• Use modern coding agents to complete and evaluate complex backend engineering tasks
• Review generated backend code for correctness, quality, maintainability, performance, and production-readiness
• Identify bugs, edge cases, architectural weaknesses, failure modes, and unclear assumptions in technical outputs
• Apply professional backend engineering judgment to realistic software engineering scenarios
• Evaluate backend implementations involving APIs, microservices, distributed systems, backend platforms, and database-backed applications
• Review service boundaries, data flow, authentication logic, error handling, performance considerations, and integration patterns
• Assess architectural trade-offs related to scalability, reliability, maintainability, and long-term system design
• Provide structured feedback on backend design decisions and implementation quality
• Compare outputs from multiple coding agents and assess their strengths, weaknesses, accuracy, and practical usefulness
• Identify where generated solutions succeed, where they fail, and where additional engineering judgment is required
• Evaluate whether model-generated code reflects real-world backend engineering standards
• Document review findings clearly for project teams and quality evaluation workflows
• Produce clear, structured evaluations of backend engineering tasks and generated outputs
• Explain reasoning around code quality, system design, performance, maintainability, and architectural trade-offs
• Support technical assessment workflows by documenting accepted work, improvement areas, and practical engineering conclusions
• Help ensure outputs reflect production-scale backend engineering expectations

Skills

• 2+ years of professional backend engineering experience
• Hands-on experience building APIs, distributed systems, microservices, backend platforms, or database-backed applications
• Regular use of AI coding agents such as Cursor, Claude Code, Codex, Windsurf, Gemini CLI, or similar tools
• Ability to evaluate generated code and identify bugs, edge cases, architectural trade-offs, and performance issues
• Strong understanding of backend architecture, service design, database interaction, testing, reliability, and maintainability
• Clear written communication skills and comfort documenting technical reasoning in a remote, project-based environment
• A degree in Computer Science, Software Engineering, Computer Engineering, Information Systems, or a related technical field is helpful
• Equivalent professional experience in backend engineering, distributed systems, software architecture, or production software development is also highly relevant
• Experience working on large-scale production systems is strongly preferred
• Experience with Node.js, Python, Java, Go, TypeScript, C#, Ruby, or comparable backend languages
• Familiarity with frameworks and tools such as Django, FastAPI, Spring, Express, NestJS, PostgreSQL, MySQL, MongoDB, Redis, Kafka, or comparable technologies
• Experience with cloud platforms, CI/CD pipelines, Docker, Kubernetes, observability tooling, or deployment workflows
• Background in technical code review, systems design interviews, software architecture review, or backend performance evaluation
• Strong comfort working in sprint-based project environments with focused technical assessment windows

Benefits

• Independent contractor engagement
• Fully remote and flexible scheduling
• Sprint-based, project-based availability
• Full-time or high-availability project participation may be requested depending on project scope
• Some project work may run in focused 12–24 hour sprint windows depending on project requirements
• Some projects may use accepted-task compensation depending on the specific workflow
• Payments are made weekly via Stripe or Wise based on services rendered
• Projects may be extended, shortened, adjusted, or concluded based on project needs and performance
• Work must not involve sharing confidential or proprietary information from any employer, client, or institution

Company Overview