Lead AI Systems Review Engineer (Remote Contractor)

AuraOne Human Data; United States; Remote; USD 83,000 - 152,000; Full time

Job summary

AuraOne, Inc. is seeking a Principal / Lead Systems Engineer for AI Systems Review. This remote contract role involves evaluating production code and AI outputs, reproducing failures, and writing tests to guide model improvements.

You will grade solutions for correctness, style, and edge cases, and document failure modes to help the modeling team target gaps. We expect strong engineering experience, concise test-writing ability, and clear, reasoned review notes.

Qualifications

• Strong day-job engineering experience and ability to read, run, and debug unfamiliar code.
• Comfort writing concise unit tests that capture a single failure mode.
• Familiarity with a testing framework: pytest, Jest, JUnit, Go test, RSpec, etc.
• Clear written reasoning in review notes to convince another senior engineer.
• Reliable async availability for at least 10 hours per week.
• Prior code-review or technical-interview-grading experience is a plus.

Responsibilities

• Run and reproduce candidate code outputs in a sandboxed environment for assignments.
• Grade engineering review solutions for correctness, style, and edge-case handling.
• Write minimal failing tests demonstrating bugs.
• Compare paired solutions and rank them with written rationale.
• Tag failure modes (compile error, runtime crash, edge-case issues) with severity.
• Document recurring code-generation failures for the modeling team.
• Calibrate against gold-standard reviews to maintain high inter-rater reliability.

Skills

Code review

Debugging

Unit testing

Software engineering

Engineering review

Testing judgment

Tools

pytest

Jest

JUnit

Go test

RSpec

Job description

AuraOne, Inc. is seeking a Principal / Lead Systems Engineer for AI Systems Review. This remote contract role involves evaluating production code and AI outputs, reproducing failures, and writing tests to guide model improvements.

You will grade solutions for correctness, style, and edge cases, and document failure modes to help the modeling team target gaps. We expect strong engineering experience, concise test-writing ability, and clear, reasoned review notes.