Senior DevOps Reviewer: AI Code Quality & Debugging

AI Trainer Jobs

United States

Remote

USD 153,000 - 207,000

Full time

2 days ago
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Job summary

AI Trainer Jobs is seeking a Senior DevOps Engineer for a remote engineering review track that evaluates production code, debugging traces, and AI outputs against real-world correctness standards. You will reproduce failures, write unit tests, and explain fixes to guide the modeling team.

Expect a focus on code quality and test coverage to ensure reliable model behavior. Role involves grading solutions, drafting rationale, and identifying failure modes across cloud and platform engineering

Qualifications

  • Open-source contributions or a public portfolio that demonstrates production-quality code.
  • Experience with the target language's standard tooling, linters, and idiomatic style guides.
  • Familiarity with security-review checklists (OWASP, CWE) and AppSec patterns.

Responsibilities

  • Run and reproduce candidate code outputs in a sandboxed environment for Senior DevOps Engineer assignments.
  • Grade cloud & platform engineering solutions for correctness, style, and edge-case handling.
  • Write minimal failing tests that demonstrate the bug a model output missed.
  • Compare paired solutions and rank them with a written rationale tied to the rubric.
  • Tag failure modes (compile error, runtime crash, off-by-one, security issue) with severity scores.

Skills

Code review
Debugging
Unit testing
Software engineering judgment
Cloud & platform engineering
Software engineering

Tools

pytest
Jest
JUnit

Job description

AI Trainer Jobs is seeking a Senior DevOps Engineer for a remote engineering review track that evaluates production code, debugging traces, and AI outputs against real-world correctness standards. You will reproduce failures, write unit tests, and explain fixes to guide the modeling team.

Expect a focus on code quality and test coverage to ensure reliable model behavior. Role involves grading solutions, drafting rationale, and identifying failure modes across cloud and platform engineering

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