Senior Software Engineer - AI Code Evaluation
New
G
Gramian ConsultancyAI code evaluation
Workable locations: Bangladesh. Brazil. Colombia. Egypt. Ghana. IndiaContractSenior
Salary not disclosed
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Job Details
- Languages
- Strong written English
- Experience
- 7+ years of professional software engineering experience.
- Required Skills
- PHPPythonGitJavaRubyC#C++GoRust
Requirements
- Have 7+ years of professional software engineering experience.
- Be proficient in at least one of Python, JavaScript/TypeScript, Java, C++, Go, C#, Ruby, PHP, or Rust.
- Have significant experience building, maintaining, debugging, and reviewing production-grade software.
- Understand software design principles, clean code, modular architecture, abstraction, error handling, and maintainability.
- Be able to identify functional, performance, security, and design issues in complex codebases.
- Have strong debugging, root-cause analysis, and problem-solving skills.
- Have experience with code reviews and collaborative software development workflows.
- Be familiar with Git and modern software engineering practices.
- Have strong written English and the ability to communicate technical feedback clearly.
- Understand data structures, algorithms, APIs, databases, and application architecture.
Responsibilities
- Review and evaluate AI-generated code across programming languages and software engineering scenarios.
- Assess code for correctness, reliability, security, scalability, readability, and maintainability.
- Identify bugs, logical errors, incomplete implementations, edge-case failures, and architectural weaknesses.
- Analyze unfamiliar codebases and understand the impact of proposed changes.
- Review bug fixes, feature implementations, refactoring, API integrations, configuration changes, and database operations.
- Compare alternative implementations and determine whether they satisfy technical requirements.
- Rewrite or improve code to create high-quality reference solutions.
- Provide clear technical explanations of identified issues and recommended improvements.
- Develop evaluation criteria, technical annotations, and rubrics for code-quality assessment.
- Collaborate with researchers and engineering teams to design coding benchmarks and improve LLM evaluation methodologies.
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