Senior Software Engineer

About the RoleWe are looking for senior software engineers with 7+ years of industry experience to support the training and evaluation of large language models. In this role, you will review, analyze, and improve AI-generated code, ensuring that it is correct, secure, maintainable, scalable, and aligned with production engineering standards.

This is a code quality and engineering evaluation role—not a traditional software testing or manual QA position. You will apply your software engineering judgment to assess implementation quality, identify root causes, and recommend or implement robust solutions.

What Does Day-to-Day Look Like?

• Review and evaluate AI-generated code across different 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 which solution best satisfies the requirements.
• Rewrite or improve code to create high-quality reference solutions.
• Provide clear technical explanations for 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.Required Qualifications
• 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.
• Significant experience building, maintaining, debugging, and reviewing production-grade software.
• Strong understanding of software design principles, clean code, modular architecture, abstraction, error handling, and maintainability.
• Proven 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.
• Strong written English and the ability to communicate technical feedback clearly.
• Good understanding of data structures, algorithms, APIs, databases, and application architecture.