AI Software Engineering Domain Expert

AI Trainer Jobs; United States; Remote; USD 55,000 - 83,000; Part time

Job summary

AI Trainer Jobs is seeking a contractor for the AI Software Engineering Domain Expert track. Remote, with expected hours and task-volume defined by program needs. You will run candidate code in a sandbox, evaluate AI outputs, and document gaps with concise tests and rationale.

Ideal candidates have strong engineering chops, comfort writing unit tests, and familiarity with common testing frameworks. Remote work from the United States is supported, with hourly compensation after interview.

Qualifications

• Strong day-to-day engineering experience in software development.
• Ability to read, run, and debug unfamiliar code for evaluation tasks.
• Clear, concise reasoning when documenting findings and decisions.

Responsibilities

• Run and reproduce candidate code outputs in a sandboxed environment.
• Grade AI software engineering domain solutions for correctness and edge-case handling.
• Write the smallest failing tests that demonstrate bugs.
• Compare paired solutions and rank them with a rubric-based rationale.

Skills

Engineering experience

Unit tests

Code review

Debugging

AI domain knowledge

Tools

pytest

Jest

JUnit

Go test

RSpec

Job description

About the role

AI Software Engineering Domain Expert is a remote engineering review track for evaluating production code, debugging traces, and developer-facing AI outputs against real-world correctness standards. Reviewers reproduce failures, write the unit test the model should have written, and explain the fix so the modeling team can target the gap.
Engineering model quality lives or dies on whether the generated code actually compiles, passes tests, and handles edge cases. AuraOne pairs experienced engineers with the modeling team to grade outputs the way a code reviewer would.
Judge generated code and software engineering agents. Read their debugging traces.

Responsibilities

• Run and reproduce candidate code outputs in a sandboxed environment for AI Software Engineering Domain Expert assignments.
• Grade ai software engineering domain engineering review 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.

Role details

Track Code review & evaluation Work model Remote · Independent specialist contractor Compensation Hourly rate confirmed after the interview process. Eligible from US

What you should bring

• Strong day-job engineering experience — you can read, run, and debug unfamiliar code for AI Software Engineering Domain Expert work.
• Comfort writing concise unit tests that capture a single failure mode.
• Familiarity with a testing framework. pytest, Jest, or JUnit. Go test, RSpec, or whatever you use.
• Clear written reasoning — your review note has 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.

Role signals

Example tasks

• Reproduce a generated engineering solution to a coding task, run the test suite, and grade it.
• Write the smallest failing test that demonstrates a model's edge-case bug.
• Compare two paired solutions and rank them with a written rationale tied to the rubric.
• Triage a security issue surfaced by a model and document the patch the model should have produced.

Useful experience

• 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.

Compensation and schedule

Hourly rate confirmed after the interview process.
Expected arrangement: contractor , with program-defined task volume and review pacing. Placement depends on current program demand and reviewer confirmation.

Skills used in matching

• Code review
• Debugging
• Unit testing
• Software engineering judgment
• AI Software Engineering Domain engineering review
• Software engineering
• AI model evaluation

Application boundary

Creating a specialist profile records your experience and preferences. Starting role intake is a separate action that attaches this role to your candidate record.

Specialist intake

The intake preserves your chosen role, the visible terms, and source attribution for reviewer context.

• 01 Confirm profile and eligibility details.
• 02 Attach this role deliberately.
• 03 Receive a human review decision or follow-up.
  Placement timing depends on program demand and reviewer confirmation.