Software Engineer - AI Coding Agent Evaluation

Remote • Posted 8 hours ago • Updated 8 hours ago
Part Time
Remote
USD 35.00 per hour
Fitment

Dice Job Match Score™

🔢 Crunching numbers...

Job Details

Skills

  • Extract
  • Transform
  • Load
  • Training
  • JIRA
  • Art
  • Quality Assurance
  • Prompt Engineering
  • Software Development
  • Node.js
  • Java
  • Rust
  • Fluency
  • Docker
  • ROOT
  • Linux
  • Bash
  • Debugging
  • Shell
  • Artificial Intelligence
  • English
  • Data Science
  • Machine Learning (ML)
  • Computer Vision
  • Manual Testing
  • Technical Support
  • Scratch
  • System Administration
  • Nginx
  • cron
  • Computational Science
  • NumPy
  • PyTorch
  • DevOps
  • Git
  • Python
  • UV
  • PY
  • LLVM
  • Testing
  • Evaluation
  • PASS
  • Onboarding

Summary

Please submit your CV in English and indicate your level of English proficiency.

Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.

About the Role

You'll design coding tasks that challenge frontier AI coding agents. Each task is a self-contained Docker environment with a broken piece of software; an AI agent attempts the fix; automated tests verify the outcome. Your deliverable is the full task package: broken code, tests, instructions, and a reference solution proving the task is solvable.

Responsibilities:
  • Invent a realistic developer scenario - a real bug, a broken ETL, a missing feature - not a toy problem.
  • Build a reproducible Docker environment with pinned dependencies.
  • Write a pytest that verifies outcomes, not specific commands - deterministic, non-flaky, and does not leak the fix.
  • Write an instruction.md that reads like a Jira ticket a developer would receive.
  • Write a reference solve.sh proving the task is solvable.
  • Calibrate difficulty so current state-of-the-art agents solve the task 20-60% of the time.
  • Iterate based on feedback from expert QA reviewers.
  • Later: review other authors' tasks as a QA reviewer.

Not in scope
  • Data labeling, prompt engineering.
  • Production code to ship - you design problems and verification for AI agents.
  • Leetcode puzzles - scenarios must look like real developer work.
  • Not every candidate task ships - quality over quantity.

Requirements
  • 3+ years of production software development in one backend stack - Python, Go, Node.js, Java, or Rust. Depth in one stack beats breadth.
  • Python + pytest fluency - required regardless of primary stack. The task harness is pytest-based even when the broken app is in another language. Fixtures, parametrize, monkeypatch, timeouts, conftest.py.
  • Docker authoring - reproducible Dockerfiles, pinned dependencies, multi-stage builds when needed, non-root user.
  • Linux & Bash - comfort debugging inside containers (strace, lsof, journalctl); shell beyond set -euo pipefail.
  • AI coding agent experience - Claude Code, Cursor, Roo Code, or similar, on non-trivial work. You can cite a specific time the AI was confidently wrong and how you caught it.
  • English - B2+ written.

Not a fit
  • Data Science, ML, or Computer Vision engineers without backend-engineering output.
  • Manual QA testers without automation or test authoring.
  • Frontend-only, low-code / no-code, IT Support, or Business Analysts.
  • Engineers who have never written pytest from scratch.
  • Junior, intern, or assistant as the most recent role.

Preferred qualifications
  • Domain depth in Security, System Administration (nginx / systemd / cron), Scientific Computing (NumPy / PyTorch / SciPy), DevOps, or Git internals.
  • Modern Python tooling (uv, poetry, pyproject.toml).
  • Coverage tooling (pytest-cov, coverage.py, gcov, llvm-cov, kcov).
  • Fuzzing or property-based testing (Hypothesis).
  • Prior contribution to agent-evaluation benchmarks or related frameworks.

Process

Apply Pass qualification (90-minute sample-task screen + short behavioral interview) Join a project Complete tasks Get paid.

Time commitment
  • Onboarding: ~10 hours per first task.
  • Steady state: ~5 hours per task, 2-4 parallel tasks per author.
  • Realistic weekly load: 8-20 hours. Higher volume available for top performers.
  • You choose when and how to contribute; tasks must be submitted by the deadline and meet acceptance criteria.

Compensation:
  • Paid contributions, rates up to $35/hour*.
  • Task-based compensation equivalent to hourly rate, depending on performance and volume.
  • Some projects include incentive payments.

*Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be provided to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.

Apply

Submit your CV via the Mindrift platform. Indicate your English level, note this role (Software Engineering Evaluation Specialist - Terminal Bench), and include a GitHub profile link if available.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90934409
  • Position Id: 9dc515f315e8770b3541e65be8235383
  • Posted 8 hours ago
Create job alert
Set job alertNever miss an opportunity! Create an alert based on the job you applied for.

Similar Jobs

Remote or Chicago, Illinois

Today

Contract, Third Party

$75 - $100 hourly

Remote

Today

Easy Apply

Contract

200 - 300

Remote

Today

Easy Apply

Contract

200 - 300

Remote

Today

Easy Apply

Contract

200 - 300

Search all similar jobs