Principal / Lead Systems Engineer — AI Systems Review

AuraOne Human Data

United States

A distancia

USD 83.000 - 152.000

Jornada completa

14 días+

Una candidatura completa en un minuto

Currículum y carta de presentación personalizados, listos para enviar.

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Descripción de la vacante

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.

Formación

  • 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.

Responsabilidades

  • 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.

Conocimientos

Code review
Debugging
Unit testing
Software engineering
Engineering review
Testing judgment

Herramientas

pytest
Jest
JUnit
Go test
RSpec

Descripción del empleo

Principal / Lead Systems Engineer - AI Systems Review 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.

Why this role matters

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.

Responsibilities
  • Run and reproduce candidate code outputs in a sandboxed environment for Principal / Lead Systems Engineer - AI Systems Review assignments.
  • Grade principal / lead systems engineer 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.
  • Tag failure modes (compile error, runtime crash, off-by-one, security issue) with severity scores.
  • Document recurring code-generation failures so the modeling team can target them.
  • Calibrate against gold-standard reviews to keep inter-rater agreement above target.
Qualifications
  • Strong day-job engineering experience - you can read, run, and debug unfamiliar code for Principal / Lead Systems Engineer - AI Systems Review 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.
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.
Nice to have
  • 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.
Skills
  • Code review
  • Debugging
  • Unit testing
  • Software engineering judgment
  • Principal / Lead Systems Engineer engineering review
  • Software engineering
Work model

Remote - US-eligible. Remote - Independent specialist contractor. Employment type: CONTRACTOR. Applicants must be authorized to work from US.

Compensation

Hourly rate confirmed after the interview process.

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