Junior Software Engineer

Weekday AI
•$150 - $200•Remote

About The Position

This contractor role is for one of the client’s projects and is remote. The Junior Software Engineer will contribute to the evaluation and improvement of advanced artificial intelligence systems. The work focuses on evaluating AI-generated code for correctness, quality, efficiency, and design; creating programming problems, reference solutions, and test cases; and assessing AI models’ ability to solve real-world software engineering challenges. The role also involves reviewing AI-generated technical reasoning about debugging, architecture, and system design, then providing structured feedback to improve the reliability and performance of AI-generated solutions. It is suited to early-career software engineers with strong programming fundamentals, analytical skills, and practical software development and review experience. Prior artificial intelligence experience is not required.

Requirements

  • At least one year of professional experience as a software engineer at a well-established technology company.
  • At least part of the relevant professional experience must have been gained within the past three years.
  • Strong understanding of programming fundamentals, data structures, algorithms, and object-oriented programming.
  • Practical experience writing, debugging, testing, and reviewing code.
  • Familiarity with software development practices, including version control, code reviews, testing, and debugging.
  • Ability to assess code for correctness, performance, readability, and maintainability.
  • Foundational understanding of software architecture and system design principles.
  • Strong analytical and problem-solving skills.
  • Excellent written communication skills and ability to clearly explain technical decisions and complex engineering concepts.
  • Ability to work independently and deliver accurate, high-quality technical assessments.

Nice To Haves

  • Experience with Python, Java, C++, JavaScript, TypeScript, Go, or similar programming languages.
  • Knowledge of object-oriented programming and design patterns.
  • Experience with API development and backend engineering.
  • Knowledge of software architecture and system design.
  • Experience with performance optimization and profiling.
  • Familiarity with Git and version control.
  • Experience with unit testing and integration testing.
  • Familiarity with CI/CD and software development workflows.
  • Experience evaluating AI-generated code.
  • Familiarity with AI coding assistants and model benchmarking.
  • Professional software engineering experience at a recognized technology company.
  • Experience developing and maintaining production-quality applications, services, or APIs.
  • Familiarity with reviewing complex codebases and identifying implementation weaknesses.
  • Experience designing coding exercises, technical assessments, or automated evaluation tests.
  • Based in an English-speaking country.
  • Ability to communicate technical findings in clear, structured, and concise English.

Responsibilities

  • Review AI-generated code for functional correctness, readability, maintainability, efficiency, and alignment with software engineering best practices.
  • Design challenging programming problems that assess algorithmic thinking, debugging, implementation quality, and practical engineering judgment.
  • Develop accurate, well-structured reference solutions to software engineering problems.
  • Create comprehensive test cases to validate functionality, cover edge cases, and identify incomplete or incorrect implementations.
  • Evaluate AI-generated explanations and decisions involving software architecture, system design, debugging, and implementation strategies.
  • Identify bugs, inefficient algorithms, poor design choices, security concerns, and violations of coding standards.
  • Provide detailed, actionable feedback about errors, weaknesses, and ways to improve code quality and model performance.
  • Document problem requirements, expected behavior, solution approaches, testing procedures, and technical evaluation findings.
  • Ensure coding tasks, reference solutions, and evaluation criteria are accurate, consistent, and reproducible.
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