Senior Software Engineer - AI Code Evaluation
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 3h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 1d ago
The date the source published, not the day we noticed it (2026-10-01). Last seen at its source just now.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Bangladesh, Brazil, Colombia, Egypt, Ghana, India
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay $88.5k–136.5k/yr
Middle 50% of 24 listings that do state pay — Engineering · all levels · Brazil · USD/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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workable employer's own board first seen 4h ago · last seen just now
The listing
About Gramian
Gramian Consultancy is a boutique consultancy specializing in IT professional services and engineering talent solutions. With a strong background in software engineering and leadership, we help companies build high-performing teams by matching them with professionals who truly fit their needs.
About the Role
We are looking for senior software engineers with 7+ years of industry experience to support the training and evaluation of large language models. You will review, analyze, and improve AI-generated code, applying real-world engineering judgment to assess correctness, security, scalability, maintainability, and production quality.
This is a software engineering and code-quality evaluation role, not a traditional software testing or manual QA position. You will analyze unfamiliar codebases, identify root causes, compare alternative implementations, and create robust solutions and evaluation criteria.
SENIORITY: Senior — 7+ years
Key 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.
Requirements
- 7+ years of professional software engineering experience.
- Strong proficiency in at least one programming language, including 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 software engineering practices.
- Strong written English and ability to communicate technical feedback clearly.
- Good understanding of data structures, algorithms, APIs, databases, and application architecture.