Backend Security Engineer

This role is for one of our clients

Pay: 30–100/hour

Job Type: Contractor (~15 hrs a week)

Location: Remote

Schedule: Flexible, you pick the hours and days (including weekends if desired)

Required Skills: Python3, Java, Rust, Algorithms, Basics of C++, TypeScript, Bug fixing, Feature implementation, Codebase refactoring, Performance optimization, Pentesting, Security audit

We are seeking a skilled Backend Security Engineer to contribute to the development and evaluation of next-generation AI systems. In this role, you will use your expertise in backend engineering and application security to create realistic, complex coding tasks that assess AI systems' ability to solve real-world software engineering challenges.

You will design tasks involving backend feature implementation, bug fixes, secure coding, vulnerability remediation, and code quality improvements. You will also develop deterministic verification mechanisms that reliably accept valid solutions meeting the specified requirements and reject incorrect or incomplete implementations.

Prior experience working in AI is not required. Strong backend engineering capabilities, security expertise, and sound technical judgment are the key qualifications for success.

Requirements:

Key Responsibilities

Backend Engineering: Design, develop, modify, and debug backend services, APIs, and application components.

Security-Focused Task Development: Create challenging coding tasks involving secure software development, vulnerability fixes, authentication, authorization, and backend security controls.

Automated Verification: Implement deterministic verifiers and automated tests to validate code behavior, functional correctness, and adherence to task requirements.

Application Security: Identify and address security vulnerabilities using established practices, including OWASP guidelines and Common Weakness Enumeration (CWE) classifications.

Code Review and Analysis: Review software implementations for correctness, security risks, performance, maintainability, and adherence to engineering standards.

Debugging and Optimization: Investigate software defects, performance bottlenecks, and complex system failures in large-scale applications.

Code Refactoring: Improve existing codebases through refactoring, architectural enhancements, and implementation of complex backend features.

AI Evaluation: Develop high-quality engineering tasks that help evaluate and improve AI systems' software development, debugging, and security reasoning capabilities.

Required Qualifications

• Strong backend development experience using Java, Node.js, Go, Rust, TypeScript, Python, C++, or similar programming languages.
• Proven experience building scalable backend services, APIs, and production-grade applications.
• Strong debugging, automated testing, performance optimization, and code review skills.
• Solid understanding of software architecture, algorithms, data structures, and fundamental computer science concepts.
• Ability to identify software defects, diagnose system bottlenecks, and implement reliable solutions.
• Strong analytical thinking, problem-solving, and technical communication skills.
• Ability to work independently and exercise sound engineering judgment when solving complex technical problems.

Preferred Qualifications

• Professional experience in cybersecurity, application security (AppSec), or Security Operations (SecOps).
• Hands-on experience with penetration testing, vulnerability assessments, and security-focused code reviews.
• Knowledge of secure coding practices, OWASP Top 10, CWE classifications, and common software vulnerabilities.
• Experience identifying and remediating security flaws in backend services, APIs, and large-scale applications.
• Familiarity with security testing, automated validation, and vulnerability remediation workflows.
• Experience refactoring complex codebases and improving application reliability, scalability, and security.

Assessment and Selection Process

Candidates are expected to complete interviews and assessments independently, without outside assistance. The same standard applies to project work, where individual expertise, technical judgment, and problem-solving ability are essential.

The selection process includes:

Application submission and completion of screening questions.

An AI interview lasting approximately 30 minutes.

A technical assessment, if required.

Hiring manager review.

Compensation Structure

Compensation is output-based, with payment provided for each task that meets the defined project specifications and quality standards. Completion time may vary depending on task complexity, the engineer's experience, and individual workflow.

Minimum submission requirements apply, and selected engineers must submit a specified minimum number of tasks each week.

Start Timeline and Availability

The hiring process typically moves quickly, with positions often filled within 48 hours. Candidates should be ready to begin immediately. Following selection and onboarding, successful candidates are expected to start their first tasks within 24–48 hours.