Senior Code Quality Engineer | AI/LLM

Role & Responsibilities

• Review and evaluate AI-generated code for correctness, reliability, security, scalability, readability, and maintainability.
• Identify bugs, logical errors, incomplete implementations, edge-case failures, and architectural issues.
• Analyze unfamiliar codebases and assess the impact of proposed changes.
• Review bug fixes, feature implementations, refactoring, API integrations, database operations, and configuration changes.
• Compare alternative implementations and determine which solution best meets technical requirements.
• Rewrite or improve code to create high-quality reference solutions.
• Provide clear technical explanations for identified issues and recommended improvements.
• Create technical annotations, evaluation criteria, and rubrics for code-quality assessment.
• Collaborate with AI researchers and engineering teams to improve coding benchmarks and LLM evaluation.
• Apply practical software engineering judgment to assess AI-generated implementations.

Important: This is a code quality and engineering evaluation role, not a traditional software testing or manual QA position.

Preferred Candidate Profile

• 7+ years of professional software engineering experience.
• Strong proficiency in at least one programming language such as Python, JavaScript/TypeScript, Java, C++, Go, C#, Ruby, PHP, or Rust.
• Experience building, maintaining, debugging, and reviewing production-grade software.
• Strong understanding of software design principles, clean code, modular architecture, abstraction, error handling, and maintainability.
• Ability to identify functional, performance, security, and design issues in complex codebases.
• Strong debugging, root-cause analysis, and problem-solving skills.
• Experience with code reviews and collaborative software development workflows.
• Familiarity with Git and modern engineering practices.
• Good understanding of data structures, algorithms, APIs, databases, and application architecture.
• Strong written English and ability to communicate technical feedback clearly.