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Salary
$288k – $384k per year
Location
Remote (Burundi)
Seniority
Junior · 1+ year exp
Employment
Contractor

First seen by Alion on Oct 13, 2026.

Overview
Company
Impact
Profile match
Headquartered in Machakos, Kenya, FreshTalent is a Pan-African recruitment and talent acquisition platform. The company provides a digital job marketplace, talent sourcing services, and AI-powered recruitment tools to connect African professionals with local and global employers. By streamlining remote and cross-border hiring across sectors like technology, finance, and engineering, it helps international organizations access vetted talent while empowering job seekers across the continent.

Junior Software Engineer - AI Code Evaluation

Compensation

Annualized Compensation: $288,000-$384,000 per year

Hourly Rate: $150-$200 per hour

Employment Type: Contractor

Work Arrangement: Remote

The annualized figure is based on 40 hours per week and 48 working weeks per year. Actual earnings will depend on project workload, assignments, and hours worked.

About the Role

We are seeking junior software engineers with professional experience at leading technology companies to evaluate AI-generated code and help improve AI performance on real-world software engineering tasks.

In this role, you will assess code for correctness, quality, and design, create challenging programming problems with reference solutions and test cases, and evaluate AI reasoning across software architecture, debugging, and system design.

This opportunity is suited to software engineers who combine strong technical judgment with the ability to explain engineering decisions clearly. Your feedback will help improve the quality and reliability of AI-generated software solutions.

Key Responsibilities

  • Evaluate AI-generated code for correctness, quality, maintainability, and design.

  • Develop challenging coding problems that test practical software engineering skills.

  • Create reference solutions and test cases to assess code correctness and performance.

  • Review AI reasoning across software architecture, debugging, algorithms, data structures, and system design.

  • Identify errors, weaknesses, and opportunities for improvement in generated code and technical approaches.

  • Assess whether proposed solutions demonstrate sound engineering judgment.

  • Provide detailed technical feedback to support improvements in AI model performance.

  • Explain technical decisions and evaluation findings clearly in writing.

Required Qualifications

  • At least one year of professional software engineering experience at a leading technology company, with at least part of that experience gained within the past three years.

  • Strong understanding of software engineering fundamentals, including algorithms and data structures.

  • Knowledge of system design and software architecture.

  • Ability to review code, identify defects, and evaluate implementation quality.

  • Strong debugging and analytical problem-solving skills.

  • Ability to explain technical decisions and findings clearly in writing.

  • Based in an English-speaking country.

Preferred Qualifications

  • Experience evaluating code quality, software design, and engineering trade-offs.

  • Experience developing coding challenges, reference implementations, or test cases.

  • Familiarity with reviewing technical reasoning across debugging, architecture, and system design.

  • Ability to assess multiple approaches to a software engineering problem and identify their strengths and weaknesses.

Key Skills

  • Software Engineering

  • Code Review

  • AI-Generated Code Evaluation

  • Algorithms

  • Data Structures

  • System Design

  • Software Architecture

  • Debugging

  • Problem Solving

  • Coding Challenge Development

  • Test Case Design

  • Reference Solution Development

  • Code Correctness

  • Software Quality Assessment

  • Technical Analysis

  • Written Technical Communication

  • Critical Thinking

What Success Looks Like

  • AI-generated code is evaluated accurately for correctness, quality, and design.

  • Coding challenges, reference solutions, and test cases effectively assess software engineering capabilities.

  • Weaknesses in AI reasoning, debugging, and system design are identified and documented.

  • Technical feedback is clear, actionable, and grounded in sound engineering judgment.

  • Evaluations contribute to improved AI performance on practical software engineering tasks.

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